Image processing device and image processing device control method

FIELD: physics, computer engineering.

SUBSTANCE: invention relates to computer engineering. An image processing device for detecting, from image data generated by an image sensor formed by a plurality of pixels, a signal from a defective pixel of the image sensor comprises a first determination unit for obtaining a first determination value indicating the value of the difference in signal strength between a pixel of interest and a plurality of pixels located near the pixel of interest; a second determination unit for obtaining a second determination value indicating the distribution width of the difference in signal strength between the pixel of interest and the plurality of pixels located near the pixel of interest; and a detection unit for detecting if the signal from the pixel of interest is a signal from a detective pixel using the first determination value and the second determination value, wherein the first determination unit obtains the first determination value by obtaining the difference in signal strength between the pixel of interest and each of the plurality of pixels located near the pixel of interest, obtaining from each difference value indicating the probability that the signal from the pixel of interest is a signal from a defective pixel, and multiplying the obtained values.

EFFECT: high accuracy of detecting a defective pixel.

11 cl, 22 dwg

 

The technical field to which the invention relates.

The present invention relates to an imaging device that detects a signal from a defective pixel of the image sensor, and method of controlling the imaging device.

The level of technology

The imager, such as digital cameras or digital video cameras generally use a sensor based on charge-coupled device (CCD sensors or CMOS sensors as image sensors, which are color filters. With such image sensors, there are cases where a defective pixel (also called "defect flicker") occurs due to structural factors, factors that arise in the production process, external factors arising after production, etc. for Example, one of the examples of factors that produce defective pixels in the CMOS sensor is the appearance of noise in the floating diffusion when the charges are taken from the photodiodes. This noise does not always occur periodically, so sometimes the noise can occur at frequent intervals, such as the formation of the image every few times, and sometimes noise may occur at infrequent intervals, such as every few years. It is also known that the frequency of occurrence of defective pixels in the image sensor is not the dependent is it on temperature and accumulation time of the charge.

In this regard, methods of detecting a defective pixel in the image sensor have been proposed in patent publications Japan No. 2004-297267 and No. 2001-086517. Using these methods it is possible not only to detect defective pixels that appear in a particular place during the production process, but also defective pixels that occur after production. For example, patent publication Japan No. 2004-297267 discloses a method of obtaining, for each color filter of a difference of signal levels between the target pixel and many pixels adjacent to the target pixel, and if the difference is greater than or equal to the threshold value, determine the required pixel as a defective pixel. Patent publication Japan No. 2001-086517 discloses a method of obtaining brightness values of all pixels regardless of the color of the color filters, and if the difference in brightness levels between the target pixel and a set of neighboring pixels is greater than or equal to the threshold value, determine the required pixel as a defective pixel.

However, when using conventional technologies defective pixel, resulting in the image sensor cannot be detected with high accuracy. For example, when using the method disclosed in patent publication Japan No. 2004-297267, in that case, if you are highly sensitive to the formation of the image is Azania, the gain of the image data (image signal) increases and, accordingly, the noise component included in the image data also increases, thus, in some cases, the noise may be more noticeable than the signal levels of pixels adjacent to the pixel of interest. In particular, in the region where the spatial frequency of the object is low, there is a higher probability that this component of the noise will have a greater value than the signal levels of pixels adjacent to the pixel of interest, and as a result, the difference of signal levels between the target pixel and neighboring pixels becomes greater than a threshold, and the pixel of interest may be incorrectly identified as a defective pixel. It should be noted that although it is possible that the threshold is set high to avoid such incorrect definition, in the region where the signal level is high, it is difficult to detect a defective pixel, because the difference of signal levels between the target pixel and the neighboring pixels is small (less obvious). Problems similar to those discussed in patent publication Japan No. 2004-297267, also appear in the case of the method disclosed in patent publication Japan No. 2001-086517.

Disclosure of inventions

The present invention provides technology for the detection is of the defective pixel in the image sensor with high precision.

In accordance with one aspect of the present invention provides an imaging device for detecting from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of the image sensor containing:

the first definition block (the first definition), configured to receive the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest;

the second block definition (the second definition), configured to receive the second value definition that specifies the width of the distribution of the difference of signal levels between the target pixel and many pixels located near the pixel of interest; and

the detection unit (detection means), configured to detect whether the signal of interest from the pixel signal of the defective pixel using the first definition values and the second value definitions

in which the first block definition gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the many pixels located near the peaks of interest is I, receiving from each of the difference values indicating the probability that the signal of the pixel of interest is a signal of the defective pixel, and multiplying the obtained values

the first value determination is a value that increases with increasing magnitude of the difference, and the second value determination is a value that increases with decreasing width of the distribution of the magnitude of the difference, and

the detection unit detects the signal from the pixel of interest as a signal of the defective pixel, and when the first value and the second value of determination is greater than or equal to the threshold value.

Thus, the imaging device further comprises an error correction block (tool correction)is made with the possibility of correction of the signal level required pixel using the correction value received from the signal levels of the pixels located near the pixel of interest, when the detection unit detects the signal from the pixel of interest as a signal of the defective pixel, and further comprises:

a processing unit (processor), configured to perform processing of the high-pass filter in the field, which includes the pixel of interest, in many areas, center the bathrooms on the interested pixel,

the first definition block receives the first value is determined from the absolute values of the processed high-pass filter and

the second definition block receives the second value is determined from the width of the distribution of the absolute values of the processed high-pass filter.

In addition, in the imaging device, the processing unit performs processing of the lowpass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest, to perform processing of the lowpass filter, and

the processing unit performs processing of the lowpass filter in one direction, centered on the pixel of interest, and then performs the processing of the high-pass filter in another direction centered on the pixel of interest that is different from the direction of lay of the lowpass filter.

Thus, the imaging device further comprises:

many processing units (processing)performed by the possibility of processing high-pass filter in different frequency ranges;

many of the first block definition (first definition) and a plurality of second blocks definition (second detection tools), which are secured respectively to the many BC the OECS processing; and

block select (selector)made with a choice of values obtained from the first value definition and the second definition values obtained from the first block definition and the second definition block, which correspond to one of the processing units.

According to the second aspect of the invention provides an imaging device for detecting from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of the image sensor containing:

the first definition block, configured to receive the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest;

the second definition block, configured to receive the second value definition that specifies the width of the distribution of the difference of signal levels between the target pixel and many pixels located near the pixel of interest;

the correction unit, configured to correct, using values obtained by multiplying the first value definition and the second definition values of the signal of interest pixel by weighting and summing the level of C is Nala interested pixel and the correction value, received from the signal levels of the pixels located near the pixel of interest,

the first definition block gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the multiple pixels in the vicinity pixel of interest, receiving from each of the difference values indicating the probability that the signal from the pixel of interest is a signal of the defective pixel, and multiplying the obtained values

the first value determination is a value that increases with increasing magnitude of the difference, and the second value determination is a value that increases with decreasing width of the distribution of the magnitude of the difference, and

the correction block assigns greater weight to the correction value increases the value obtained by multiplying the first value definition and the second definition values.

Thus, the imaging device further comprises:

a processing unit configured to perform processing of the high-pass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest,

the first definition block receives the first value defined who I am from the absolute values of the processed high-pass filter and

the second definition block receives the second value is determined from the width of the distribution of the absolute values of the processed high-pass filter.

In addition, in the imaging device

a processing unit to perform processing of the high-pass filter performs the processing of the lowpass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest, and

the processing unit performs the processing of the low pass filter in one direction, centered on the pixel of interest, and then performs the processing of the high-pass filter in the other direction from centered on the pixel of interest that is different from the direction of lay of the lowpass filter.

Thus, the imaging device further comprises:

many processing units, configured to perform filter processing of the upper frequencies in different frequency ranges;

many of the first block definitions and many of the second block definitions that are provided according to the multitude of processing units; and

block selection is made with a choice of values obtained from the first value definition and the second definition values obtained by the first definition block and the second block definition, the cat is who match one of the processing units.

According to another aspect of the invention provides a control method for the image processing that detects from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of the image sensor containing:

executing the first block determining step of receiving the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest, and the first value of determination increases with increasing magnitude of the difference;

running the second unit definition step of obtaining the second value definition that specifies the width of the distribution of the magnitude of the difference in signal levels between the target pixel and many pixels located near the pixel of interest, and the second value determination increases with decreasing width of the distribution of the magnitude of the difference; and

performed by the block detection phase detection signal from the pixel of interest as a signal of the defective pixel, when the first value definition, and the second value of determination is greater than or equal to the threshold value,

at the stage of obtaining the first value defining the first b is OK definition gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the multiple pixels, in the vicinity pixel of interest, receiving from each of the difference values indicating the probability that the signal from the pixel of interest is a signal of the defective pixel, and multiplying the obtained values.

According to a fourth aspect of the invention provides a control method for the image processing that detects from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of the image sensor containing:

executing the first block determining step of receiving the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest, and the first value of determination increases with increasing magnitude of the difference;

running the second unit definition step of obtaining the second value definition that specifies the width of the distribution of the magnitude of the difference in signal levels between the target pixel and many pixels located near the pixel of interest, and the second value determination increases with decreasing width of the distribution of the magnitude of the difference; and

performed by the block correction phase correction signal of interest pixels is La by weighting and summing the signal level of the interested pixel and the correction value, received from the signal levels of the pixels located near the pixel of interest, so that the correction value is assigned a higher weight increases the value obtained by multiplying the first value definition and the second definition values

at the stage of obtaining the first value definition the first definition block gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the multiple pixels in the vicinity pixel of interest, receiving from each of the difference values indicating the probability that the signal from the pixel of interest is a signal of the defective pixel, and multiplying the obtained values.

Other aspects of the present invention will become more apparent from the following description of illustrative embodiments with reference to the accompanying drawings.

Brief description of drawings

Figure 1 is a block diagram showing the device configuration of image formation, in respect of which applies a processing device of the image forming aspect of the present invention.

Figure 2 is a block diagram showing the circuit configuration of the determination of the defective pixel in the device forming the image shown is a figure 1.

Figa-3I are diagrams illustrating processing performed by the circuit insertion of zeros, the LPF circuits and schemes HPF in the schema definition of the defective pixel, shown in figure 2.

Figure 4 is a block diagram showing the circuit configuration of the determination threshold value in the schema definition of the defective pixel, shown in figure 2.

Figa and 5B are diagrams illustrating the formation level of the defect is performed by the method of forming the defect level in the schema definition of threshold values shown in figure 4.

6 is a block diagram showing the circuit configuration of determining the correlation detection circuit defective pixel, shown in figure 2.

7 is a graph illustrating the formation of the second values of the determination performed by the method of forming the defect level in the schema definition of the correlation shown in Fig.6.

Fig is a block diagram showing the circuit configuration of the correction of the defective pixel in the device forming the image shown in figure 1.

Fig.9 is a block diagram showing another circuit configuration of the detection of the defective pixel in the device forming the image shown in figure 1.

Figa and 10B are graphs illustrating the HPF processing, the tasks performed by the fifth circuit HPF and the sixth circuit HPF in the scheme of detecting a defective pixel, shown in Fig.9.

11 is a block diagram showing another circuit configuration of the detection of the defective pixel in the device forming the image shown in figure 1.

The implementation of the invention

Preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be noted that the same reference position denote the same elements in all the drawings, and repeated description will not be presented.

Figure 1 is a block diagram showing the configuration of the device 100 imaging, where applicable, the imaging device comprising an aspect of the present invention. The device 100 of the image-forming is a forming device of the image to capture an image of the object and is implemented in the present embodiment, in a digital camera.

The device 100 of forming the image includes a lens 101 of image formation, the aperture 102, the sensor 103 images, which are R (red), G (green) and b (blue) color filters, and circuit 104 analog-to-digital conversion (A/D conversion), which converts the analog image signal (electric signal)received from the sensor 103 image, the digital data of the images. The device 100 imaging also includes circuit 105 detection of defective pixel acting as a device image processing that detects the signal from the defective pixel (such as defect flicker) in the sensor 103 of the image. The device 100 imaging also includes circuit 106 correction of the defective pixel, which performs the correction signal, which was determined by the circuit 105 detection of defective pixel as an output signal from the defective pixel. The device 100 imaging also includes circuit 107 memory management, which performs the bus arbitration between the circuits, DRAM 108 that temporarily stores image data, and circuit 109 of the image processing, which performs image processing, such as processing, color conversion processing and sharpening. The device 100 imaging also includes a circuit 110 scale, which reduces or enlarges the image data, the system controller 111, which defines the parameters and mode of each circuit, and block 112 display that displays (reproduces) the image corresponding to the image data. The device 100 imaging also includes circuit 113 modulation of the video, which modulates the image signal, that is about to reproduce the image at block 112 display, and circuit 114 compression, which performs the compression processing of image data. The device 100 imaging also includes removable media 115 write, which writes the image data that has been compressed by the circuit 114 compression, and circuit 116 controls the media that serves as an interface with the carrier 115 entries.

The light falling on the lens 101 imaging (light object), falls on the sensor 103 image after appropriate exposure through aperture 102 and is converted into an electrical signal by the sensor 103 of the image. The electric signal of the light of the object generated by the sensor 103, the image is converted from an analog image signal into digital image data by the circuit 104 A/D conversion.

Image data, compiled by the signals received from multiple pixels, and is formed by the sensor 103 of the image and the circuit 104 A/D conversion, are entered into the scheme 105 detection of a defective pixel that detects the signal of the defective pixel included in the image data. The signal detected by the circuit 105 detection of defective pixel as an output signal from the defective pixel is included in the circuit 106 correction of the defective pixel, which adjusts the signal by interpolation with reference to the signals from the pixels located near the pixel that was identified to the to be defective.

The image data received by the circuit 106 correction of the defective pixel correction signal is detected as an output signal from the defective pixel is written to DRAM 108 with schema 107 memory management. Image data which is written to the DRAM 108, the read circuit 109 of the image processing by using the schema 107 memory management.

In scheme 109 image processing the image data read from the DRAM 108, processed color conversion and processing, sharpness, etc. and converted into image data that includes a luminance signal and color difference signal. The image data processed by the circuit 109 of the image processing are recorded in the DRAM 108 with schema 107 memory management. The image data recorded on the DRAM 108, the read circuit 110 scale with schema 107 memory management.

Scheme 110 zoom changes the magnification of the image data to, for example, 720×240 to display an image corresponding to image data, at block 112 of the display. The image data enlarged or reduced by the circuit 110 scale, written to DRAM 108 with schema 107 memory management. The image data recorded on the DRAM 108, the read circuit 113 modulation video with schema 107 memory management.

Scheme 113 modulation video vypolnyaetsya image data. The image data processed by the circuit 109, the image processing is displayed as an image on the unit 112 of the display.

In that case, when data is written to the media 115 write circuit 110 zoom increases or decreases the size of the image data that have been read from the DRAM 108 (image data that has been read after processing circuit 109 image processing and write to the DRAM 108), to the specified size. Image data, the increase of which was changed by the circuit 110 scale, written to DRAM 108 with schema 107 memory management. Image data which is written to the DRAM 108, the read circuit 114 compression with schema 107 memory management.

Scheme 114 compression compresses the image data which have been read from the DRAM 108, using this method of compression, such as JPEG. The image data compressed by the circuit 114 compression, written to DRAM 108 using circuit 107 controls the memory and then read circuit 116 controls the media. The circuit 116 controls the media writes the image data compressed by the circuit 114 compression, media 115 entries.

With reference to figure 2 details the scheme 105 detection of a defective pixel that detects the signal from the defective pixel in the sensor 103 of the image using image data generated by sensor 103 of images and patterns 104 A/D p is obrazovaniya. As mentioned above, since the sensor 103 image posted by the array of color filters of the Bayer array, the image data generated by the sensor 103 of the image and the circuit 104 A/D conversion, are composed of many kinds (three kinds of R, G and b) groups of monochrome pixels. It should be noted that in the present embodiment, the description is given using as an example the case where a defective pixel (defective flicker) is one of the pixels G, is taken as the pixel of interest.

Scheme 105 detection of defective pixel takes the input signal is digitized image data from the circuit 104 A/D conversion. It is assumed that the signal level of each pixel included in the image data is represented by 8 bits. Scheme 105 detection of the defective pixel includes circuit 201 insertion of zeros, the first circuit 202 lowpass filter (LPF), a second circuit LPF 203, the third circuit LPF 204 and the fourth circuit 205 LPF. Scheme 105 detection of defective pixel also includes a first circuit 206 of the high-pass filter (HPF), a second circuit 207 HPF, the third circuit 208 HPF and the fourth circuit 209 HPF. Scheme 105 detection of defective pixel further includes a first circuit 210 of the absolute value (ABS), a second circuit 211 ABS, third circuit 212 ABS and the fourth circuit 213 ABS. Scheme 105 detection of defective pixel additionally includes is a diagram 214 forming the luminance signal, circuit 215 definition of defect, the circuit 216 define the threshold values (the first block definitions), circuit 217 determine the correlation (the second block definitions), the multiplier 218 and the selector 219.

Circuit 201 insertion of zeros, as shown in figa, inserts a zero value (0) in the signal levels of the pixels other than the pixels G (pixels having a color different from the color pixel of interest) in the field, composed of a set of pixels centred on the pixel of interest.

The first circuit LPF 202, as shown in figv, performs the processing of the low pass filter in the vertical direction (for example, processing of the lowpass filter using the filter coefficient (1, 2, 1)) of the image data in which a value of zero was inserted in the signal levels of the pixels other than pixels of G. as a Consequence, the signal levels of the pixels with a zero value, the interpolated signal levels of their respective vertical pixels.

The second circuit LPF 203, as shown in figs performs LPF processing in the horizontal direction on the image data in which a value of zero was inserted in the signal levels of the pixels other than pixels of G. as a Consequence, the signal levels of the pixels with a zero value, the interpolated signal levels of their respective horizontal pixels.

rata scheme LPF 204, as shown in fig.3D performs LPF processing in the 135-degree direction on the image data in which a value of zero was inserted in the signal levels of the pixels other than pixels of G. as a Consequence, the signal levels of the pixels with a zero value, the interpolated signal levels of their respective pixels in a 135-degree direction.

The fourth circuit LPF 205, as shown in fige performs LPF processing in the 45-degree direction on the image data in which a value of zero was inserted in the signal levels of the pixels other than pixels of G. as a Consequence, the signal levels of the pixels with a zero value, the interpolated signal levels of their respective pixels in a 45-degree direction.

The first circuit 206 HPF, as shown in fig.3F, performs the processing of the high-pass filter in the horizontal direction (for example, processing of the high-pass filter using the filter coefficient (-1, 2, -1) on the result (output) of the LPF processing performed by the first circuit LPF 202.

The second circuit 207 HPF, as shown in fig.3G, performs the processing of the high-pass filter in the vertical direction on the result (output) of the LPF processing performed by the circuit 203 of the second LPF.

The third circuit 208 HPF, as shown in fign, performs the processing shown that the and upper frequencies in the 45-degree direction on the result (output) of the LPF processing, made the third circuit 204 LPF.

The fourth circuit 209 HPF, as shown in Fig, performs the processing of the high-pass filter 135-degree direction on the result (output) of the LPF processing performed by the fourth circuit 205 LPF.

In this case, the circuit 105 detection of the defective pixel, the first circuit LPF 203 and the first circuit 206 HPF comprise a processing module for performing filter processing in different directions, using the pixel of interest as a reference. Similarly, the second circuit LPF 203 and the second circuit 207 HPF, the third circuit LPF 204 and the third circuit 208 HPF and the fourth circuit LPF 205 and the fourth circuit 209 HPF respectively comprise a processing unit for performing filter processing. It should be noted that the direction of processing LPF (first direction) and the direction of the HPF processing (the second direction, orthogonal to the first) is different for each of the processing modules.

The first circuit 210 ABS outputs 8-bit absolute value of the result (output) of the HPF processing performed by the circuit 206 of the first HPF. Similarly, the second circuit 211 ABS, the third circuit 212 ABS and the fourth circuit 213 ABS output 8-bit absolute value of the results (output) of the HPF processing performed by the second circuit 207 HPF, the third circuit 208 HPF and the fourth circuit 209 HPF, respectively. The absolute values of the results of the treatments is key HPF, performed first-fourth circuits 206-209 HPF, refer respectively to HA1, HA2, HA3 and HA4.

The circuit 214 forming the luminance signal generates a brightness signal from the image data entered into the scheme 105 detection of defective pixels (image data composed of R, G and b of the Bayer array). For example, the circuit 214 forming the luminance signal generates a brightness signal Y in accordance with equation 1 below.

Scheme 215 definition of defect displays the defect flag indicating whether the signal of interest from the pixel signal of the defective pixel, in accordance with the sign (plus or minus) of the results of the HPF processing performed first-fourth circuits 206-209 HPF. Scheme 215 definition of defect also displays black-and-white flag, indicating whether the defective pixel of white defect or a black defect. Here "white defect" refers to the defective pixel in the dark looks bright, and "black defect" refers to a defective pixel, which appears as black under incident light.

In particular, in the case when all the results of the HPF processing performed first-fourth circuits 206-209 HPF, have the same sign, the scheme 215 definition of defect displays the flag 1 as the defect flag (1 bit). This means that the signal from the pixel of interest is the signal of the m a defective pixel. On the other hand, in the case where any of the results of the HPF processing performed first-fourth circuits 206-209 HPF has a different sign, the scheme 215 definition displays the defect flag is "0" as the flag of the defect. This means that the signal from the pixel of interest is not a signal of the defective pixel. It should be noted that the flag of the defect is used as the select signal of the selector 219.

In the case when the results of the HPF processing performed first-fourth circuits 206-209 HPF, have the plus sign, the scheme 215 definition displays the defect flag is 1, indicating a white defect, as black-and-white flag (1 bit). On the other hand, in the case when the results of the HPF processing performed first-fourth circuits 206-209 HPF, have the sign "minus", schema 215 definition displays the defect flag is 0, indicating that a black defect, as black-and-white flag. This black-and-white flag was not always necessary and can be skipped. It should be noted that black-and-white flag is displayed to the circuit 216 determine the threshold value.

The circuit 216 define the threshold values compares the absolute value with HA1 on HA4 results of the HPF processing, which were introduced from the first-fourth circuits 210-213 ABS, respectively, with an arbitrarily set threshold value. Based on the results of a comparison circuit 216 determination threshold value PE displays the signal value determining D1, which is the value indicating the probability that the signal from the pixel of interest is a signal of the defective pixel.

Figure 4 is a block diagram showing the circuit configuration 216 define the threshold values. The circuit 216 determining the threshold value includes a first circuit 401 of formation of the defect, the second circuit 402 of formation of defect, the third circuit 403 of formation of defect, the fourth circuit 404 of formation of defect and multipliers with 405 through 407.

The first circuit 401 of formation of defect generates (calculates) the defect level DL1, based on an absolute value H1 of the HPF processing (processing of horizontal filter), which was introduced from the first circuit 210 ABS. The second circuit 402 of formation of defect generates (calculates) the level of the defect DL2 based on the absolute value of the HA2 of the HPF processing (processing of the vertical filter), which was introduced from the second circuit 211 ABS. The third scheme 4 03 the formation of defect generates (calculates) the level of the defect DL3, based on an absolute value HA3 of the HPF processing (processing 45-degree filter), which was introduced from the third circuit 212 ABS. The fourth circuit 404 of formation of defect generates (calculates) the level of the defect DL4, based on the absolute values of the AI HA4 of the HPF processing (processing 135-degree filter), which was introduced from the fourth circuit 213 ABS. It is assumed that each of these absolute values HA1-HA4 results of the HPF processing is represented by 8-bit value.

Specific description of the formation of the defect level, carried out the first-fourth circuits 401-404 of formation of defect is given with reference to figa and 5B. It should be noted that the term "defect level"used herein refers to the value indicating the probability that the signal from the pixel of interest is a signal of the defective pixel. In the present embodiment, the level of the defect is formed as a value in the range from 0 to 255, and the defect level "0" indicates that the signal from the pixel of interest is not a signal of the defective pixel. Conversely, the defect level "255" indicates that the signal from the pixel of interest is a signal of the defective pixel. Than the level of the defect is closer to "0", the higher the probability that the signal from the pixel of interest is not a signal of the defective pixel, whereas the level of the defect is closer to "255", the higher the probability that the signal from the pixel of interest is a signal of the defective pixel.

Figa and figv demonstrate the relationship between the absolute value of the HPF processing, which is introduced in the first-fourth circuits 401-404 the formation of the level of the defect, and the defect level (value), formed the first-fourth circuits 401-404 of formation of the defect. On figa and figv horizontal axis denotes the absolute value of HA (HA1-HA4) as a result of the HPF processing, and the vertical axis denotes the level of the defect DL (DL1-DL4).

First-fourth circuits 401-404 of formation of defect fix in advance a threshold value T shown in figa and 5B, and the slope value SL1. First-fourth circuits 401-404 of formation of defect convert the absolute value of the HPF processing in the defect level DL (8 bits) in accordance with equations 2-4, below.

When

When

When

Here TN=TN+(255/SL1).

For example, shown in figa and 5B examples, if the input of the absolute value of the HPF processing is greater than or equal to the threshold value, the first-fourth circuits 401-404 formation of defect level form level defect DL with a value of "255". On the other hand, if the input of the absolute value of the HPF processing is less than or equal to the threshold value TN, first-fourth circuits 401-404 formation of defect level form level defect DL with a value of "0". If the input absolute value of the PF processing more than the threshold value TH2 and less than the threshold value TH1, the first-fourth circuits 401-404 formation of defect level form level defect DL with the same value, which increases with the input of the absolute value of the HPF processing.

It should be noted that the first and fourth circuits 401-404 formation of defect level change threshold value TH1 and the slope SL1 in accordance with the black-and-white flag, introduced from schema 215 definition of defect, i.e. depending on whether the defective pixel of white defect or a black defect. For example, when the defective pixel is a white defect, the first-fourth circuits 401-404 formation of defect level sets the threshold value TH2 and the slope SL1 so that they have the characteristics shown in figa, and if the defective pixel is a black defect, the first-fourth circuits 401-404 formation of defect level sets the threshold value T and the slope SL1 so that they have the characteristics shown in figv.

It is assumed that the threshold value TH2 is a value obtained by multiplying the arbitrarily set value, which is determined, for example, the operating mode of the device 100 forming the image and the average value of luminance of pixels near the pixel of interest, sformirovannykh 214 forming the luminance signal. The threshold value TH2 needs to change in accordance with the luminance signal generated by circuit 214 forming the luminance signal (i.e. noise), because the higher the brightness, the more noise. When increasing the threshold value TH2 to increase the brightness, it is possible to prevent erroneous making noise for the defective pixel. In addition, it is assumed that the slope SL1 is also a value obtained by multiplying the arbitrarily set value, which is determined, for example, the operating mode of the device 100 forming the image, and the luminance signal generated by circuit 214 forming the luminance signal. The threshold value TH1 is determined by determining the threshold value TH2 and the slope SL1. It should be noted that the level of the defect DL relative to the absolute values, as shown in figa and figv may be pre-stored in the table instead of getting by transformation using equations 2-4.

Alternatively, instead of setting the threshold values TH1 and TH2, the ratio between the absolute value of HA and the level of the defect DL can be defined as function (such as a cubic function), in which the level of the defect DL increases with increasing absolute values, in the whole range of absolute values. Then this function can be switched is in accordance with brightness, so the value of the defect level DL relative to the absolute values decrease with increase the brightness of the pixels near the pixel of interest.

The multiplier 405 receives a 16-bit value by multiplying the level of the defect, formed the first circuit 401 of formation of the defect, and the defect level generated by the second circuit 402 formation of defect level, performs a procedure of 8-bit shift over a 16-bit value and outputs the resulting 8-bit value as the level of the defect DL5. The multiplier 406 receives a 16-bit value by multiplying the level of the defect, formed the third circuit 403 of formation of the defect, and the defect level, formed the fourth circuit 404 formation of defect level, performs a procedure of 8-bit shift over a 16-bit value and outputs the resulting 8-bit value as the level of the defect DL6. The multiplier 407 receives a 16-bit value by multiplying the level of the defect DL5 obtained by multiplying the multiplier 405, and defect level DL6 obtained by multiplying the multiplier 406, performs a procedure of 8-bit shift over a 16-bit value and outputs the resulting 8-bit value as the first value definition D1.

Thus, the circuit 216 define the threshold values obtains, based on the processing results of the filter, the difference of signal level is between the target pixel and many pixels, located near the pixel of interest. Then, the circuit 216 define the threshold values to form a first value determining D1, indicating that the greater the difference, the higher the probability that the signal from the pixel of interest is a signal of the defective pixel.

Returning to figure 2, it should be noted that the circuit 217 determine the correlation compares the magnitude of absolute values HA1-HA4 results of the HPF processing, which were introduced respectively from the first-fourth circuits 210-213 ABS. Based on the results of a comparison circuit 217 determine the correlation outputs the second value definition D2 indicating the probability that the signal from the pixel of interest is a signal of the defective pixel.

6 is a block diagram showing the circuit configuration 217 definition of correlation. Circuit 217 determining the correlation includes a first circuit 601 choice, a second circuit 602 choice, the third circuit 603 choice, the fourth circuit 604 choice, the fifth circuit 605 choice, the sixth circuit 606 choice, myCitadel 607 and circuit 608 determine the level of the defect.

The first circuit 601 choice compares the absolute value of the HA1 of the HPF processing, which was introduced from the first circuit 210 ABS, and the absolute value of HA2 of the HPF processing, which was introduced from the second circuit 211 ABS, and displays a larger absolute value is selected. The second circuit 602 choice compares the absolute value of the HA1 of the HPF processing, which was introduced from the first circuit 210 ABS, and the absolute value of HA2 of the HPF processing, which was introduced from the second circuit 211 ABS, and outputs a smaller absolute value.

The third circuit 603 selection compares the absolute value HA3 of the HPF processing, which was introduced from the third circuit 212 ABS, and the absolute value HA4 of the HPF processing, which was introduced from the fourth circuit 213 ABS, and outputs the greater absolute value. The fourth circuit 604 choice compares the absolute value HA3 of the HPF processing, which was introduced from the third circuit 212 ABS, and the absolute value HA4 of the HPF processing, which was introduced from the fourth circuit 213 ABS, and outputs a smaller absolute value.

The fifth circuit 605 choice compares an absolute value that is derived from the first circuit 601 of choice, and an absolute value that is derived from the third circuit 603 selection, and outputs the greater absolute value. The absolute value that is derived from the fifth circuit 605 choice is the maximum absolute value among the results of the HPF processing performed first-fourth circuits 210-213 ABS (i.e. the results of the filter processing performed in four directions).

The sixth circuit 606 choice compares an absolute value that is derived from the second circuit 602 choice and an absolute value that is derived from the fourth circuit 604 choice, and outputs a smaller absolute value. The absolute value that is derived from the sixth circuit 606 choice is the minimum absolute value among the results of the HPF processing performed first-fourth circuits 210-213 ABS (i.e. the results of the filter processing performed in four directions).

MyCitadel 607 subtracts an absolute value that is derived from the sixth circuit 606 choice of the absolute values derived from the fifth circuit 605 choice. The result of the subtraction performed by vycitalem 607 denotes the maximum difference (the width of the distribution of the difference among the results of the HPF processing performed first-fourth circuits 210-213 ABS, and will always be a positive value greater than or equal to zero, because that is obtained by subtracting the minimum of the absolute value of the maximum absolute value.

Circuit 608 to determine the level of defect generates (calculates) the second value definition D2, based on an absolute value, extracted from myCitadel 607, and outputs the second value definition D2. The formation of the second definition values D2 obtained by the circuit 608 to determine the level of defect specifically described with reference to Fig.7. It should be noted that as the first value determining D1, the second value definition D2, SF is armirovannoj circuit 608 to determine the level of defect, specifies the probability that the signal from the pixel of interest is a signal of the defective pixel. Fig.7 is a graph showing the relationship between the result of the subtraction performed by vycitalem 607 (absolute value HB), which must be entered into the scheme 608 determine the level of the defect, and the second is the definition D2 generated by the circuit 608 to determine the level of defect. 7, the horizontal axis indicates the result of the subtraction performed by vycitalem 607 (absolute value HB), and the vertical axis indicates the second value definition D2.

Circuit 608 determine the level of the defect in advance stores a threshold value T and the slope value SL2, as shown in Fig.7, and converts the result of the subtraction vicites 607 second value definition D2 (8 bits) in accordance with equations 5-7, below.

In that case, if HB≤TH3,

In that case, if TH3≤HB≤TH4,

In that case, if TH4≤HB,

For example, as shown in Fig.7 example, if the HB subtracting vycitalem 607 is less than or equal to the threshold value TH3, the circuit 608 to determine the level of defect forms a second value definition D2 "255". On the other hand, if the result of HB subtracting vycitalem 607 is greater than or equal to ogbomo value TH4, circuit 608 to determine the level of defect forms a second value definition D2, is equal to 0. If the result of subtracting vycitalem 607 is greater than a threshold TH3 and less than the threshold value TH4, the circuit 608 to determine the level of defect forms a second value definition D2 in such a way that it increases as the result of subtracting vycitalem 607 (absolute value) decreases.

It should be noted that the threshold value TH3 is a value obtained by multiplying the arbitrarily set value, which is determined, for example, the operating mode of the device 100 forming the image, and the luminance signal generated by circuit 214 forming the luminance signal. It should also be noted that the slope SL2 is a value obtained by multiplying the arbitrarily set value, which is determined, for example, the operating mode of the device 100 forming the image, and the luminance signal generated by circuit 214 forming the luminance signal. The threshold value TH4 is determined by determining a threshold T and values of the slope SL2. Alternatively, the second value definition D2, depending on the result of HB subtracting vycitalem 607, as shown in Fig.7, may be previously stored in the table instead of getting using adjusted the th 5-7.

Thus, the circuit 217 determine the correlation obtains, based on the processing results of the filter, the width of the distribution of the difference of signal levels between the target pixel and pixels near him (i.e. the result of subtracting HB). Circuit 217 determine the correlation then generates the second value definition D2, indicating that less than the above width of the distribution of the difference, the higher the probability that the signal from the pixel of interest is a signal of the defective pixel.

It should be noted that if the image data included a lot of noise, there is a probability that the circuit 216 define the threshold values may incorrectly identify the signal from the pixel of interest as a signal of the defective pixel (i.e. the output of the first definition values constituting 255) due to noise. In view of this, in the scheme 217 definition of correlation is required to detect the signal from the pixel of interest so that it was not the signal of the defective pixel in the case, if image data in a region that includes a pixel of interest included a lot of noise and width of the distribution of the difference is large.

In that case, if the interest pixel is not defective, the results of the HPF processing, obtained using the first-fourth circuits 210-213 ABS (i.e. the results of the filter processing, carried out the in four directions) will have the value close to zero and accordingly the width of the distribution of the difference will have a value close to zero. In this case, the circuit 217 determine the correlation may not be able to detect the signal from the pixel of interest as a signal of the defective pixel (i.e. the output of the first definition values constituting 255), because the width of the distribution of the difference is small. For this reason, in the circuit 216 define the threshold values it is necessary to detect the signal from the pixel of interest as a signal of the defective pixel if the difference of signal levels between the target pixel and the neighboring pixels is greater than or equal to the threshold value.

Therefore, in the present embodiment, as shown in figure 2, the multiplier 218 receives the third value determine by multiplying the first value determining D1, extracted from the schema 216 determination threshold value and the second value definition D2, extracted from the schema 217 define the threshold values. In particular, the multiplier 218 receives a 16-bit value by multiplying the first value determining D1 and the second value definition D2, provides the procedure for 8-bit shift over a 16-bit value and outputs the resulting 8-bit value (i.e. a value from 0 to 255) as the third value to determine K. This allows the circuit 217 definition of good correlation is Asim way to determine whether the pixel of interest is defective, even if the schema 216 define the threshold values made an erroneous decision. In other words, in the scheme 216 define the threshold values, and in the scheme 217 determine the correlation, if desired pixel was identified as a defective pixel of interest is detected as defective. Alternatively, and in the schema 216 define the threshold values, and in the scheme 217 determine the correlation, if it was determined that there is a high probability that the signal from the pixel of interest is a signal of the defective pixel signal from the pixel of interest is detected as a signal with high probability represents the signal of the defective pixel.

The selector 219 outputs a third value To determine, obtained by multiplication with the multiplier 218, if the defect flag, introduced from schema 215 definition of defect is "1" (that is, indicates that the pixel of interest is defective). If the defect flag, introduced from schema 215 definition of defect is 0 (that is, indicates that the interest pixel is not defective), the selector 219 outputs "0" as the third meaning of the definition. It should be noted that the level of the defect, which is derived from the selector 219, is introduced into the circuit 106 correction of the defective pixel.

Fig is a block CX is mu showing the circuit configuration 106 correction of the defective pixel. Scheme 106 correction of the defective pixel receives input of image data that includes the defective pixel, by using the circuit 104 A/D conversion. Scheme 106 correction of the defective pixel includes a circuit 801 calculate correction values and circuit 802 weighted adder.

Circuit 801 calculate the correction value performs, for example, processing filter using coefficient (for example, (1, 0, 1)), which does not refer to a specific pixel, and calculates a correction value for correcting the signal level of the defective pixel. Alternatively, the circuit 801 calculate the correction value can determine the edge direction from the image data and calculate a correction value with reference to the signal levels of the pixels along the edge direction of the pixel of interest, or to obtain the correction value by pre-interpolation. As another alternative, the correction value can be obtained by assigning a larger weight to the correction value calculated on the basis of the signal levels of the pixels along the boundary direction than the weight of the correction value calculated on the basis of signal levels of pixels along the other directions, and summation and the FCP is in these correction values.

Circuit 802 weighted adder weights and sums the level of the ORG signal of interest of the pixel extracted from the circuit 104 A/D conversion, and the value of COR correction calculated by the scheme 801 calculating the correction value in accordance with a third value To determine derived from the schema 105 detection of defective pixels. For example, circuit 802 weighted adder outputs the adjusted level of the OUT signal of interest pixel in accordance with equation 8 below.

As described above, the third value definition varies from 0 to 255. When the third value To determine becomes close to zero, if there is a high likelihood of interest to the pixel is not defective (i.e. the interest pixel is a normal pixel), circuit 802 weighted adder outputs the level of the OUT signal (that is, image data in which a defective pixel has been corrected) by assigning a large weight to the level of the ORG signal of interest pixel and summing the weighted level of the ORG signal and values C0R correction. On the other hand, when the third value determination To become close to "255", if there is a high probability that the pixel of interest is defective, the circuit 802 weighted adder outputs the level is b OUT signal by assigning a large weight to the value of COR correction interested pixel and summing the weighted values COR correction and level ORG signal pixel of interest. Alternatively, the third value definition may be compared with a predetermined threshold, and if the third value To determine less than the threshold value, the output level of the ORG signal pixel of interest as the adjusted level of the OUT signal, and otherwise outputs the value obtained in accordance with equation 8 as the adjusted level of the OUT signal.

In accordance with this option run as described above and in scheme 216 define the threshold values, and in the scheme 217 determining the correlations of interest pixel is detected as a defective pixel in the case if the signal from the pixel of interest was defined as the signal of the defective pixel. Alternatively, as in the circuit 216 determination threshold value, and circuit 217 determine the correlation, if it was determined that there is a high probability that the signal from the pixel of interest is a signal of the defective pixel, the signal of interest pixel is detected as the level of the signal with high probability represents the signal of the defective pixel. For this reason, the defective pixel can be detected with higher accuracy than when using traditional methods. In addition, the defective pixel can be corrected with more high the accuracy, than when using traditional methods, because the signal of interest pixel is corrected in accordance with a value obtained by multiplying the level of the defect extracted from the schema 216 determination threshold value, and the defect level, extracted from the schema 217 definition of correlation.

It should be noted that in the circuit 105 detection of the defective pixel, as shown in Fig.9, the first circuit LPF 202 and the second circuit LPF 203, each may be provided with two circuits of the high-pass filter, each of which performs various processing high-pass filter.

Referring to Fig.9, the fifth circuit 901 HPF and the sixth circuit 902 HPF, each performs different processing high-pass filter in the horizontal direction above the LPF processing performed by the first circuit LPF 202. For example, as shown in figa, the fifth circuit 901 HPF carries out the processing of the high-pass filter using coefficient of the low pass filter((1, 2, 1) × ( 1, 2, 1), × (-1, 2, -1)) (the first processing high-pass filter using a first high-pass filter). The sixth circuit 902 HPF, as shown In figure 10, performs the processing of the high-pass filter using coefficient of the high-pass filter((1, 2, 1) × (-1, 2, -1), × (-1, 2, -1)) (the second processing high-pass filter using the second high-pass filter).

edema circuit 903 HPF and the eighth circuit 904 HPF, each carried out by different processing high-pass filter in the vertical direction above the LPF processing performed by the second circuit LPF 203. For example, the seventh circuit 903 HPF carries out the processing of the high-pass filter using coefficient of the low pass filter (see figa). The eighth circuit 904 HPF performs the processing of the high-pass filter using coefficient of the high-pass filter (see figv).

The fifth circuit 905 ABS displays the absolute value of the result (output) of the HPF processing performed by the fifth circuit 901 HPF. Similarly, the sixth circuit 906 ABS, the seventh circuit 9 07 ABS and the eighth circuit 908 ABS deduce the absolute values of the results (output) of the HPF processing performed, respectively, the sixth circuit 902 HPF, the seventh circuit 903 HPF and the eighth circuit 904 HPF.

The first arithmetic circuit 909 and the second arithmetic circuit 910 have the same configuration, each of them includes circuit 216 determine the threshold circuit 217 determine the correlation and the multiplier 218. The first arithmetic circuit 909 receives the input signal of the absolute values of the results of the HPF processing obtained by the fifth circuit 905 ABS, the seventh circuit 907 ABS, third circuit 212 ABS and the fourth circuit 213 ABS. The second arithmetic circuit 910 receives an input signal of the absolute values of the results of the HPF processing, the floor is obtained by using the sixth circuit 906 ABS, the eighth circuit 908 ABS, third circuit 212 ABS and the fourth circuit 213 ABS.

The first arithmetic circuit 909 and the second arithmetic circuit 910, each receive the value of determination, indicates the probability that the signal from the pixel of interest is a signal of the defective pixel using the absolute values of the results of the HPF processing performed in the same lane. It should be noted that the ideal option is to use the same lanes for all directions, including horizontal, vertical, 45-degree direction and a 135-degree direction. In the present embodiment, between the horizontal and vertical directions and the 45-degree and 135-degree directions (oblique lines) using different filter coefficients, because the distance from the pixel of interest to the specified pixel differs between the inclined and horizontal directions and vertical directions, and for this reason the frequency range between them is different.

Scheme 911 selecting the maximum value compares the value of determination, derived from the first arithmetic circuit 909, and the value of determination, derived from the second arithmetic circuit 910, and outputs a larger value definition.

If the filter is in the range of high frequencies on the data from the expression (see figv), there are cases where the boundary is and accordingly the signal from the pixel of interest is erroneously determined as a signal of the defective pixel. For this reason, the filter is also in the range of low frequencies, in order to reliably detect a defective pixel exists in the lower ranges of frequencies. Then for such a defective pixel, which exists at the boundary, the result of processing high-pass filter and the processing result of the lowpass filter compare to prevent an erroneous determination of the border as a defective pixel.

In the present embodiment, although the case where a defective pixel is detected among the pixels G, and has been described as an example, even if a defective pixel is detected, among pixels of R, or, it is possible to detect a defective pixel using a similar processing by inserting zero values in the pixels other than R or In pixels.

The circuit 216 define the threshold values and circuit 217 determine the correlation can obtain first and second values to determine, using the luminance signal Y obtained from equation 1, instead of receiving the first and second values determined by recognition among pixels G, R and B.

The absolute value ON the used circuit 216 define the threshold values obtained for the I first definition values D1, can be obtained in another way, while it indicates the difference of signal levels between the target pixel and many pixels located near the pixel of interest. For example, the circuit 216 define the threshold values may obtain an average value of absolute values of the results of the HPF processing performed first-fourth circuits 210-213 ABS, and get the first value definition D1 from equations 2-4, using the average value as an absolute value.

Circuit 217 definition of correlation can obtain the variance of the absolute values of the results of the HPF processing performed first-fourth circuits 210-213 ABS, and can be set to determine D2 to a larger value as the amount of this dispersion.

It should be noted that although the circuit 105 detection of the defective pixel is configured by the LPF circuits and schemes HPF in figure 2, it is also possible configuration, which does not include the LPF circuit, as shown in figure 11. The following is a description of the other configuration schemes 105 detection of defective pixel shown at 11, with a focus on the differences in configuration from the circuit 105 detection of the defective pixel, shown in figure 2.

The first circuit 1101 HPF performs processing HPF using the filter coefficient(-1, 0, 2, 0, -1), for example, in the horizontal direction on d is the R image, in which the signal levels of the pixels other than the pixels G, was inserted a null value. Similarly, the first circuit 1101 HPF also performs the HPF processing on the image data, in which was inserted a null value in the signal levels of the pixels other than pixels of R, and the image data, in which was inserted a null value in the signal levels of the pixels other than the pixels Century

The second circuit 1102 HPF performs processing HPF using the filter coefficient(-1, 0, 2, 0, -1), for example, in the vertical direction on the image data, in which the signal levels of the pixels other than the pixels G, was inserted a null value. Similarly the second circuit 1102 HPF also performs the HPF processing on the image data, in which was inserted a null value in the signal levels of the pixels other than pixels of R, and the image data, in which was inserted a null value in the signal levels of the pixels other than the pixels Century

The third circuit 1103 HPF performs processing HPF using the filter coefficient (-1, 2, -1), for example, in the 45-degree direction on the image data, in which the signal levels of the pixels other than the pixels G, was inserted a null value.

The fourth circuit 1104 HPF performs processing HPF using the filter coefficient (-1, 2, -1), for example, a 135-degree voltage is the t to the image data, in which the signal levels of the pixels other than the pixels G, was inserted a null value.

When the configuration circuit 105 detection of defective pixel shown figure 11, the circuit 201 insertion of zeros does not perform interpolation processing on the pixels, in which was inserted a null value, and consequently each of the schemes HPF has a coefficient of a filter which is not affected by the pixels, in which was inserted a null value during processing HPF. Both the horizontal and vertical directions can be used the same filter coefficient for the pixels G, R and b, because all of the pixels G, R and b are located across one. On the other hand, as a 45-degree and 135-degree directions only pixels G are objects for processing HPF, because the pixels G are arranged in series, whereas the pixels R and the pixels are located across one.

First-fourth circuit 1105-1108 ABS deduce absolute values (output data) of the results of the HPF processing performed respectively the first-fourth circuits 1101-1104 HPF.

Similar to the diagram 215 definition of the defect shown in figure 2, the circuit 1109 determine defect displays the flag of the defect and black-and-white flag in accordance with the sign (plus or minus) of the results of the HPF processing performed first-fourth circuits 1101-1104 HPF. If interesuiusi the pixel is a pixel G, scheme 1109 detect defects refers to the signs of the results of the HPF processing performed by the first circuit 1101 of the first HPF, the second circuit 1102 HPF, the third circuit 1103 HPF and the fourth circuit 1104 HPF. If interested pixel is a pixel R or scheme 1109 detect defects refers to the signs of the results of the HPF processing performed by the first circuit 1101 HPF and the second circuit 1102 HPF.

Similar to the diagram 216 define the threshold values shown in figure 2, the circuit 1110 determine thresholds compares the absolute values of the results of the HPF processing, which were introduced from the first-fourth circuits 1105-1108 ABS, with an arbitrarily set threshold value. Based on the results of a comparison circuit 1110 determine thresholds displays the first value determining D1, which is the value indicating the probability that the signal from the pixel of interest is a signal of the defective pixel. Similar to the diagram 217 determining the correlations shown in figure 2, the circuit 1111 determine the correlation compares the magnitude of absolute values of the results of the HPF processing, which were introduced respectively from the first-fourth circuits 1105-1108 ABS. Based on the results of a comparison circuit 1111 determine the correlation outputs the second value definition D2 indicating the probability that the signal from the pixel of interest which is the signal of the defective pixel.

If interested pixel is a pixel G, the circuit 1110 determine the threshold values and the circuit 1111 determine the correlation refers to the absolute values of the results of the HPF processing obtained by the first circuit 1105 7ABS, the second circuit 1106 ABS, third circuit 1107 ABS and the fourth circuit 1108 7ABS. If interested pixel is a pixel of the R or b, the circuit 1110 determine the threshold values and the circuit 1111 determine the correlation refers to the absolute values of the results of the HPF processing obtained by the first circuit 1105 7ABS and the second circuit 1106 ABS.

Then, as in the case of figure 2, the multiplier 218 receives the third value determine by multiplying the first value definition and the second definition values, and the third value definition is introduced into the circuit 106 correction of the defective pixel by using the selector 219.

In addition, it is also possible configuration in which the circuit 105 detection of the defective pixel is configured by a difference schemes, as shown in Fig, instead of filter circuits, such as circuit LPF and HPF scheme shown in figure 2. The following description relates to the configuration schema 105 detection of defective pixel shown in Fig, with a focus on how it differs in configuration from the circuit 105 detection of defective pixel shown in figure 2.

The first circuit 1201 difference is processing the RA is a surface to get the value by subtracting from the value of the interest pixel value of the second pixel, to the right of the interested pixel and having the same color as the pixel of interest. The second circuit 1202 difference is processing the difference to get the value by subtracting from the value of the interest pixel value of the second pixel located left of the pixel of interest and having the same color as the pixel of interest.

The third circuit 1203 difference is processing the difference to get the value by subtracting from the value of the interest pixel value of the second pixel located above the pixel of interest and having the same color as the pixel of interest. The fourth circuit 1204 difference is processing the difference to get the value by subtracting from the value of the interest pixel value of the second pixel below the pixel of interest and having the same color as the pixel of interest.

The fifth circuit 1205 difference is processing the difference to get the value by subtracting from the value of the interest pixel value of the adjacent pixel located on the right above the pixel of interest and having the same color as the pixel of interest. The sixth circuit 1206 difference is processing the difference to get the value by subtracting from the value of the interesting pixel values of adjacent pixels located the military left below the pixel of interest and having the same color what interested pixel.

The seventh circuit 1207 difference is processing the difference to get the value by subtracting from the value of the interest pixel value of the adjacent pixel located on the left top pixel of interest and having the same color as the pixel of interest. The eighth circuit 1208 difference is processing the difference to get the value by subtracting from the value of the interest pixel value of the adjacent pixel located on the right below the pixel of interest and having the same color as the pixel of interest.

Thus, each of the first-eighth circuits 1201-1208 difference obtains the difference value between the target pixel and the pixel located in the vicinity pixel of interest. Although the first-fourth circuit 1201-1204 difference process difference regardless of whether the interest pixel by pixel G, R or b, and the fifth to the eighth circuit 1205-1208 difference produce processing difference only if the interest pixel is a pixel G.

First, the eighth circuit 1209-1216 ABS deduce the absolute values of the results (output) processing the difference, made the first-eighth circuits 1201-1208 difference, respectively.

Similar to the diagram 215 definition of the defect shown in figure 2, scheme 1217 determine defec is and displays the flag of the defect and black-and-white flag in accordance with the sign (plus or minus) of the processing results of the difference, first-eighth circuits 1201-1208 difference. If interested pixel is a pixel G, the scheme 1217 detect defects refers to the signs of the results of processing the difference, made the first-eighth circuits 1201-1208 difference. If interested pixel is a pixel R or scheme 1217 detect defects refers to the signs of the results of processing the difference, made the first-fourth circuits 1201-1204 difference.

Similar to the diagram 216 define the threshold values shown in figure 2, the circuit 1218 determine thresholds compares the absolute values of the results of processing differences that were introduced from the first-eighth circuits 1209-1216 ABS, with an arbitrarily set threshold value. Based on the results of a comparison circuit 1218 determine thresholds displays the first value definition, which is the value indicating the probability that the signal from the pixel of interest is a signal of the defective pixel. Similar to the diagram 217 determining the correlations shown in figure 2, scheme 1219 determine the correlation compares the magnitude of absolute values of the results of the processing differences that were introduced respectively from the first and eighth circuits 1209-1216 ABS. Based on the results of a comparison circuit 1111 determine the correlation outputs the second value definition wide-angle is, indicates the probability that the signal from the pixel of interest is a signal of the defective pixel.

It should be noted that if the interest pixel is a pixel G, the scheme 1218 determine the threshold values and the scheme 1219 determining the correlations refer to the absolute values of the results of processing to the difference obtained by the first-eighth circuits 1209-1216 ABS. If interested pixel is a pixel R or scheme 1218 determine the threshold values and the scheme 1219 determining the correlations refer to the absolute values of the results of processing to the difference obtained by the first-fourth circuits 1209-1212 ABS.

Then, as in the case of figure 2, the multiplier 218 receives the third value determine by multiplying the first value definition and the second definition values, and the third value definition is introduced into the circuit 106 correction of the defective pixel by using the selector 219.

As described above, the circuit 105 detection of the defective pixel, in accordance with this option run, gets the first value of determination indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest. The first value determination is a value that increases as increases the difference between the signal levels is La between the target pixel and neighboring pixels. Scheme 105 detection of defective pixel receives the second value definition that specifies the width of the distribution of the magnitude of the difference in signal levels between the target pixel and a set of neighboring pixels. The second value determination is a value that increases as decreases the width of the distribution of the difference of signal levels between the target pixel and neighboring pixels. Scheme 105 detection of defective pixel multiplies the first value determining D1 and the second value definition D2 and determines that the larger the value obtained by the multiplication, the higher the probability that the signal from the pixel of interest is a signal of the defective pixel. It should be noted that if the value obtained by the multiplication, greater than or equal to the threshold value circuit 105 detection of the defective pixel can detect the signal from the pixel of interest as a signal of the defective pixel. Alternatively, the circuit 105 detection of the defective pixel can detect the signal from the pixel of interest as a signal of the defective pixel if both values determine, and D1 and D2, is greater than or equal to the threshold value.

In addition, after the circuit 106 correction of the defective pixel determines, based on the value obtained by multiplying the degree in which you have to in order to rectirostris pixel of interest, or, to correct or no interest pixel, it is possible more precisely to decrease the influence of the defective pixel, than when using traditional methods.

It should be noted that the defective pixel does not always occur separately, and there is a probability, that two defective pixels exist side by side. With this in mind, if the pixel signal is close to the signal of interest pixel, but very different from the signals of the neighboring pixels present in the vicinity of interest of the pixel circuit 105 detection of the defective pixel can perform the determination of the defective pixel with the exception of the signal level of the pixel.

In addition, although the above embodiments of the have been described using the example of processing for detecting a defective pixel is performed by the forming device of the image, such as a digital camera or camcorder, the present invention should not be limited. For example, a personal computer with the installed application is equipped with advanced image processing features, can realize the above-described processing on the image signal received from the removable storage device or over a network, in accordance with the program read from the memory (not shown).

In addition, in the present embodiment, chaturvedi defect, schema-generated definition of threshold values, and the level of the defect generated by the schema definition of correlation, are 8-bit, both defect level can have a different bit width.

Aspects of the present invention can also be implemented by a computer system or device (or devices such as a CPU or MPU)that reads out and executes a program recorded on a memory device to perform the functions of the above embodiments, or a method, the steps of which are performed by a computer system or device, such as reading or executing a program recorded on a memory device to perform the functions of the above-described embodiments. To this end, the program is provided to the computer for example via a network or from a recording means of various types serving as the memory device (that is, machine-readable means).

While the present invention has been described with reference to exemplary embodiments perform, it should be clear that the invention is not limited to the disclosed exemplary embodiments of execution. The volume of the following claims must comply with the broadest interpretation to encompass all such modifications and equivalent structures and functions.

Under this proposal Ispra is foreseen priority based on patent application of Japan No. 2010-073472, filed March 26, 2010, which is hereby incorporated herein by reference in full.

1. The imaging device for detecting from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of an image sensor, comprising:
the first definition block, configured to receive the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest;
the second definition block, configured to receive the second value definition that specifies the width of the distribution of the difference of signal levels between the target pixel and many pixels located near the pixel of interest; and
a detection unit, configured to detect whether the signal of interest from the pixel signal of the defective pixel using the first definition values and the second value definitions
in which the first block definition gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the many pixels located near the pixel of interest, receiving from each of the difference values, points is the total probability of the signal pixel of interest is a signal of the defective pixel, and multiplying the obtained values,
the first value determination is a value that increases with increasing magnitude of the difference, and the second value determination is a value that increases with decreasing width of the distribution of the magnitude of the difference, and
the detection unit detects the signal from the pixel of interest as a signal of the defective pixel, and when the first value and the second value of determination is greater than or equal to the threshold value.

2. The imaging device according to claim 1, additionally containing block correction made with the possibility of correction of the signal level required pixel using the correction value received from the signal levels of the pixels located near the pixel of interest, when the detection unit detects the signal from the pixel of interest as a signal of the defective pixel.

3. The imaging device according to claim 1, additionally containing:
a processing unit configured to perform processing of the high-pass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest,
the first definition block produces the t first value is determined from the absolute values of the processed high-pass filter and
the second definition block receives the second value is determined from the width of the distribution of the absolute values of the processed high-pass filter.

4. The imaging device according to claim 3, in which
the processing unit performs processing of the lowpass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest, to perform processing of the lowpass filter, and
the processing unit performs processing of the lowpass filter in one direction, centered on the pixel of interest, and then performs the processing of the high-pass filter in another direction centered on the pixel of interest that is different from the direction of lay of the lowpass filter.

5. The imaging device according to claim 3, further comprising:
many processing units, configured to perform filter processing of the upper frequencies in different frequency ranges;
many of the first block definitions and many of the second block definitions that are provided according to the multitude of processing units; and
block selection is made with a choice of values obtained from the first value definition and the second definition values obtained from the first block definition and the second definition block which correspond to one of the processing units.

6. The imaging device for detecting from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of an image sensor, comprising:
the first definition block, configured to receive the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest;
the second definition block, configured to receive the second value definition that specifies the width of the distribution of the difference of signal levels between the target pixel and many pixels located near the pixel of interest;
the correction unit, configured to correct, using values obtained by multiplying the first value definition and the second definition values of the signal of interest pixel by weighting and summing the signal level of the interested pixel and the correction value obtained from the signal levels of the pixels located near the pixel of interest,
the first definition block gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the set of pixels for which lizotte from the pixel of interest, receiving from each of the difference values indicating the probability that the signal from the pixel of interest is a signal of the defective pixel, and multiplying the obtained values,
the first value determination is a value that increases with increasing magnitude of the difference, and the second value determination is a value that increases with decreasing width of the distribution of the magnitude of the difference, and
the correction block assigns greater weight to the correction value increases the value obtained by multiplying the first value definition and the second definition values.

7. The imaging device according to claim 6, further comprising:
a processing unit configured to perform processing of the high-pass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest,
the first definition block receives the first value is determined from the absolute values of the processed high-pass filter and
the second definition block receives the second value is determined from the width of the distribution of the absolute values of the processed high-pass filter.

8. The imaging device according to claim 7, in which
a processing unit to perform processing is the high-pass filter, performs the processing of the lowpass filter in the field, which includes the pixel of interest, in many directions, centered on the pixel of interest, and
the processing unit performs the processing of the low pass filter in one direction, centered on the pixel of interest, and then performs the processing of the high-pass filter in the other direction from centered on the pixel of interest that is different from the direction of lay of the lowpass filter.

9. The imaging device according to claim 7, further comprising:
many processing units, configured to perform filter processing of the upper frequencies in different frequency ranges;
many of the first block definitions and many of the second block definitions that are provided according to the multitude of processing units; and
block selection is made with a choice of values obtained from the first value definition and the second definition values obtained by the first definition block and the second block definitions that correspond to one of the processing units.

10. Control method for image processing that detects from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of the image sensor, with whom containing a series:
executing the first block determining step of receiving the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest, and the first value of determination increases with increasing magnitude of the difference;
running the second unit definition step of obtaining the second value definition that specifies the width of the distribution of the magnitude of the difference in signal levels between the target pixel and many pixels located near the pixel of interest, and the second value determination increases with decreasing width of the distribution of the magnitude of the difference; and
performed by the block detection phase detection signal from the pixel of interest as a signal of the defective pixel, when the first value definition, and the second value of determination is greater than or equal to the threshold value,
at the stage of obtaining the first value definition the first definition block gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the multiple pixels in the vicinity pixel of interest, receiving from each of the difference values indicating the probability that the signal from wondering what th pixel is a signal of the defective pixel, and multiplying the obtained values.

11. Control method for image processing that detects from the image data generated by the image sensor, formed by a set of pixels, a signal from a defective pixel of an image sensor, comprising:
executing the first block determining step of receiving the first definition values indicating the difference of signal levels between the target pixel and many pixels located near the pixel of interest, and the first value of determination increases with increasing magnitude of the difference;
running the second unit definition step of obtaining the second value definition that specifies the width of the distribution of the magnitude of the difference in signal levels between the target pixel and many pixels located near the pixel of interest, and the second value determination increases with decreasing width of the distribution of the magnitude of the difference; and
performed by the block correction phase correction signal of interest pixel by weighting and summing the signal level of the interested pixel and the correction value obtained from the signal levels of the pixels located near the pixel of interest, so that the correction value is assigned more weight as to who is astania values, obtained by multiplying the first value definition and the second definition values
at the stage of obtaining the first value definition the first definition block gets the first value of determination by obtaining the difference of signal levels between the target pixel and each of the multiple pixels in the vicinity pixel of interest, receiving from each of the difference values indicating the probability that the signal from the pixel of interest is a signal of the defective pixel, and multiplying the resulting value.



 

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7 cl, 8 dwg

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