Method and apparatus for image encoding and decoding using large transformation unit

FIELD: physics.

SUBSTANCE: method of decoding an image comprises steps of: determining hierarchically structured encoding units for decoding an image, a prediction unit and a transformation unit; obtaining transformation coefficients from a bitstream through analysis and restoring encoded data of at least one prediction unit by performing entropy decoding, inverse quantisation and inverse transformation of the transformation coefficients obtained by analysis; performing intra-prediction or mutual prediction of the restored encoded data and restoring the encoded video.

EFFECT: high efficiency of compressing, encoding and decoding images.

4 cl, 18 dwg

 

The technical field to which the invention relates

Exemplary embodiments of the invention relate to a method and apparatus for encoding and decoding image, and in particular to a method and apparatus for encoding and decoding image by converting the image in the pixel area in the coefficients in the frequency domain.

The level of technology

In order to compress the image, the majority of methods and devices for encoding and decoding image coding the image by converting the image in the pixel area coefficients in the frequency domain. Discrete cosine transform (DCT), which is one of the methods of frequency conversion, is a well-known technique that is widely used in compression of image or sound. A method of image encoding using DCT, for implementing DCT on an image in the pixel area, forming a discrete cosine coefficients, quantizing the generated discrete cosine coefficients and performing entropy coding on the generated discrete cosine coefficients.

Summary of the invention

The solution of the problem

Exemplary embodiments of the provide a method and apparatus for encoding and decoded�I image using a more efficient discrete cosine transform (DCT), and also provide a computer readable recording medium recorded therein a program for executing the method.

Useful results of the invention

In accordance with one or more exemplary variants of implementation of the ability to set up unit conversion so that it was larger than the unit of prediction, and perform the DCT so that the image is efficiently compressed and encoded.

Brief description of the drawings

The above and other signs of the exemplary embodiments will become more apparent from the description of their approximate variants of implementation with reference to the accompanying drawings, in which:

Fig.1 is a block diagram of an apparatus for encoding a picture according to an exemplary variant of implementation;

Fig.2 is a diagram of the device for decoding image in accordance with another exemplary variant of implementation;

Fig.3 is a diagram of the hierarchical coding unit in accordance with another exemplary variant of implementation;

Fig.4 is a block diagram of an image encoder based on the encoding unit in accordance with another exemplary variant of implementation;

Fig.5 is a block diagram of the decoder of the image based on the encoding unit in accordance with another exemplary variant of implementation;

Fig illustrates a maximum coding unit, subunit coding, and the prediction unit in accordance with another exemplary variant of implementation;

Fig.7 is a diagram of the units of coding units and transformation in accordance with another exemplary variant of implementation;

Fig.8A and 8B illustrate a form of division of the maximum coding unit, prediction unit and unit conversions in accordance with another exemplary variant of implementation;

Fig.9 is a block diagram of a device for encoding images in accordance with another exemplary variant of implementation;

Fig.10 is a diagram of the conversion module;

Fig.11A-11C illustrate the types of conversion units in accordance with another exemplary variant of implementation;

Fig.12 illustrates different units conversion in accordance with another exemplary variant of implementation;

Fig.13 is a block diagram of the device for decoding image in accordance with another exemplary variant of implementation; and

Fig.14 is a block diagram of the sequence of operations of a method of encoding an image according to an exemplary variant of implementation;

Fig.15 is a block diagram of the sequence of operations of a method of decoding images in accordance with another exemplary variant of the implementation.

Disclosure of the invention

In con�accordance with an aspect of an exemplary embodiment of the invention a method of image encoding, including operations, which specify unit conversion by selecting the plurality of adjacent prediction units transform the set of neighboring prediction units into a frequency region in accordance with unit conversion, form the coefficients of the frequency components, quantuum coefficients of frequency components, and perform entropy encoding on the quantized coefficients of the frequency components.

The operation, which specify the unit conversion can be performed based on depth, indicating the degree of size reduction that occurs gradually from the maximum coding unit of the current macroblock or sequence of the current frame to the subunit encoding that contains the set of neighboring prediction units.

The operation, which specify the unit conversion can be performed by selecting the plurality of adjacent prediction units on which prediction is performed according to the same prediction mode.

The same prediction mode may be the mode of mutual prediction or mode of internal predictions.

The encoding of the image may further include the operation, which specify the optimal unit conversion through repeated execution wiseup� - mentioned operations on different units of conversion, the above-mentioned operations include operations which specify unit conversion by selecting the plurality of adjacent prediction units transform the set of neighboring prediction units into a frequency region in accordance with the unit conversion form and the coefficients of frequency components, quantuum coefficients of frequency components, and perform entropy encoding on the quantized coefficients of the frequency components.

In accordance with another aspect of an exemplary embodiment of the proposed device for encoding a picture, comprising a conversion module to set units conversion by selecting the plurality of adjacent prediction units, convert the plurality of adjacent prediction units into a frequency region in accordance with unit conversion and the formation of the coefficients of the frequency components, the quantization module to quantize the coefficients of the frequency components and the entropy coding module to perform entropy coding on the quantized coefficients of the frequency components.

In accordance with another aspect of an exemplary embodiment of a method of decoding images including operations, which perform entropy decoding to�of fficients frequency components, which is formed through the transformation into frequency domain in accordance with unit conversion, perform inverse quantization of the coefficients of the frequency components, perform the inverse transform of the coefficients of the frequency components in the pixel region and recreate many of the neighboring prediction units contained in the unit conversion.

In accordance with another aspect of an exemplary embodiment of the proposed device decoding image includes an entropy decoder to perform entropy decoding of the coefficients of the frequency components, which are formed by the transformation into frequency domain in accordance with the unit conversion module of inverse quantization for inverse quantization of the coefficients of the frequency components in the pixel region and the restoration of the plurality of adjacent prediction units contained in the unit conversion.

In accordance with another aspect of an exemplary variant implementation is provided a computer readable recording medium recorded therein a program for executing methods of encoding and decoding the image.

The implementation of the invention

Next, with reference to the accompanying drawings will be described an exemplary implementation options. In an exemplary� embodiments, the term "unit" can refer, or may not relate to a single unit of a certain size, depending on the context in which it is used, and the term "image" may denote a still image (frame) in relation to a video or a moving image, that is the video itself.

Fig.1 is a block diagram of an apparatus 100 for encoding an image according to an exemplary variant of the implementation.

According To Fig.1, the device 100 includes a module 110 of the separation of the maximum coding unit, the module 120 to determine the depth of encoding, the encoder 130 of the image data and an encoder 140 information encoding.

The module 110 of the separation of the maximum encoding unit may perform the division of the current frame or a sequence of macroblocks, based on the maximum coding unit that is a coding unit of the largest size. That is, the module 110 of the separation of the maximum encoding unit may perform the division of the current frame or a sequence of macroblocks to obtain at least one maximum coding unit.

In accordance with an exemplary variant of the implementation unit of encoding can be represented using a maximum coding unit and a depth. As described above, the maximum coding unit indicates the unit of encoding with the �rupen size among the coding units of the current frame, and the depth indicates the size of the subunit encoding obtained through hierarchical reduction of the unit of encoding. With the growth of the depth of the coding unit may be reduced in size from the maximum encoding unit to the minimum coding unit, wherein the depth of the maximum coding unit is defined as the minimum depth, and the depth of the minimum coding unit is defined as the maximum depth. Because the size of the coding unit decreases from a maximum coding unit as the depth increases, the subunit encoding of the kth depth may include multiple subunits encoding (k+n) th depth (k and n are integers equal to or greater than 1).

With the growth of the size of the frame that should be encoded, the encoding of the image in a larger coding units may lead to a higher degree of compression. However, if a larger unit of encoding is fixed, then the image cannot be efficiently encoded, given the ever-changing characteristics of the image.

For example, when coded even field, such as the sea or the sky, the larger the unit of encoding, the greater may be the degree of compression. However, when encoded complex area, such as people or buildings, the smaller the unit of encoding,the greater may be the degree of compression.

Thus, in accordance with an exemplary variant of the implementation for each frame or a sequence of macroblocks is set different maximum unit of encoding image and different maximum depth. Since the maximum depth denotes the maximum number of times, which may decrease the unit of encoding, the size of each minimum coding unit included in a maximum coding unit, may be set variably in accordance with a maximum depth of.

The module 120 to determine the depth of encoding specifies the maximum depth. The maximum depth may be determined on the basis of the calculation of the cost of Distortion to the Transmission Rate (R-D). The maximum depth may be determined differently for each frame or sequence of macroblock or for each maximum units of encoding. A certain maximum depth is provided to the encoder 140 information encoding, and image data according to maximum coding units are provided to the encoder 130 of the image data.

The maximum depth denotes a unit of encoding with a smaller size, which may be included in the maximum coding unit, i.e., the minimum unit of encoding. In other words, the maximum coding unit may be split into�ena on subunit encoding, having different sizes, based on different depths. This is described in more detail below with reference to Fig.8A and 8B. In addition, subunit encoding of different size, which are included in the maximum coding unit may predskazivati or be transformed based on processing units having different sizes. In other words, the device 100 may perform multiple processing operations for encoding image based on processing units having different sizes and different shapes. To encode the image data, it performs such processing operations as prediction, transform and entropy coding, wherein for each operation can be used handling units of the same size or for each operation can be used handling units of different sizes.

For example, the device 100 may select for the prediction unit of the coding unit of processing different from the unit of encoding.

When the size of the coding unit is 2N×2N (where N is a positive integer), processing units for prediction may be 2N×2N, 2N×N, N×2N and N×N. in Other words, motion prediction may be performed based on the processing unit having a shape whereby at least one of the height or width of a coding unit is divided into 2 equal parts. �alley, a handling unit, which is the basis for the prediction, is defined as a "prediction unit".

The prediction mode may be at least one internal mode, the mutual mode and skip, and the specific prediction mode can be performed with reference to only the prediction unit of a specific size and shape. For example, the internal mode can only be performed in relation to the units of predictions of size 2N×2N and N×N, the shape of which is square. Additionally, the mode with a pass can only be performed with respect to the prediction unit size of 2Nx2N. If the encoding unit there are many units of predictions, after performing prediction for each prediction unit may select the prediction mode with the lowest coding errors.

Alternatively, the device 100 may perform frequency transformation on image data based on processing units having a size other than one encoding. With regard to frequency conversion in the unit of encoding frequency transformation may be performed on the basis of the handling unit having a size equal to or smaller than the size of the unit of coding. Further, a handling unit, which is the basis for frequency conversion, is determined�Xia as "units conversion". The frequency transform may be a Discrete Cosine Transform (DCT) or the Conversion of Caruana-Loeve (KLT).

The module 120 to determine the depth of encoding can determine the subunit encoding included in the maximum coding unit, by using RD optimization based on Lagrange multiplier. In other words, the module 120 to determine the depth of encoding may determine the form of a plurality of encoding subunits obtained by splitting the maximum coding unit, wherein the multiple encoding subunits have different sizes according to their depths. The encoder 130 generates the image data bit stream by encoding the maximum coding unit on the basis of the forms of separation, i.e. forms that share the maximum coding unit, as defined by the module 120 to determine the depth of encoding.

The encoder 140 information encoding encodes information about the encoding mode for the maximum coding unit determined by the module 120 to determine the depth of encoding. In other words, the encoder 140 information encoding produces a bit stream by encoding information about the form of splitting the maximum coding unit, information about a maximum depth and information about the encoding mode subunits coding for to�each depth. Information about the mode of encoding subunit encoding may include information about a prediction unit subunit encoding information about the prediction mode for each prediction unit, and information about unit conversion subunit encoding.

Since each maximum coding unit are present subunit encoding different sizes, and information about the encoding mode must be defined for each subunit encoding, for one maximum coding unit may be determined information about at least one encoding mode.

The device 100 can form a subunit coding by dividing equally as height and width of the maximum coding unit into two in accordance with increase of depth. That is, when the size of the unit of encoding the k-th depth is 2N×2N, the size of the unit of coding (k+1)-th depth is N×N.

Thus, the device 100 in accordance with an exemplary variant of the implementation can determine the best form of separation for each maximum coding unit based on the size of the maximum coding units and a maximum depth, given the characteristics of the image. Through variable adjustment of the size of the maximum coding unit based product�of eristic image and encoding the image by splitting the maximum coding unit into subunits encoding different depths can be more effectively encoded image for various resolutions.

Fig.2 is a block diagram of an apparatus 200 for decoding an image according to an exemplary variant of the implementation.

According To Fig.2, the device 200 includes a module 210 receiving the image data, the module 220 retrieve information encoding and the decoder 230 of the image data.

The module 210 receiving the image data receives the image data based on the maximum coding units by analyzing the bit stream received by the device 200, and outputs the image data decoder 230 of the image data. The module 210 receiving the image data can extract information about a maximum coding unit of the current frame or a sequence of macroblocks from the header of the current frame or a sequence of macroblocks. In other words, the module 210 receiving the image data and divides the bit stream on maximum units of encoding so that the decoder 230 of the image data can decode the image data based on the maximum units of encoding.

Module 220 retrieve information encoding by analyzing the bit stream by the device 200, extracts from the header of the current frame information of the maximum coding unit, a maximum depth, the form of splitting the maximum coding unit, the encoding mode subunits to�of tiravanija. Information about the form of the separation and information about the encoding mode are provided to the decoder 230 of the image data.

Information about the form of splitting the maximum coding unit may include information about the encoding subunits of different size on the basis of depths included in the maximum coding unit, and information about the encoding mode may include information about a prediction unit on the basis of the subunits encoding information about the prediction mode and information about units conversion.

The decoder 230 of the image data restores the current frame by decoding the image data of each maximum coding unit based on the information extracted by the module 220 retrieve information encoding. The decoder 230 of the image data can decode subunit encoding included in the maximum coding unit, based on the information about the form of splitting the maximum coding unit. The decoding process may include a prediction process including intra prediction and motion compensation, and inverse transformation process.

The decoder 230 of the image data performs intra prediction or mutual prediction based on the information about the prediction unit and information about the mode of the forecast�Oia for to predict the prediction unit. The decoder 230 of the image data can also perform the inverse transform for each subunit coding on the basis of information about the unit conversion subunit encoding.

Fig.3 illustrates a hierarchical encoding unit in accordance with an exemplary variant of the implementation.

According To Fig.3 hierarchical encoding unit in accordance with an exemplary variant of implementation may include the coding unit whose width × height are 64×64, 32×32, 16×16, 8×8, and 4×4. Besides these coding units with fully square shape may exist units of coding, which width / height are 64×32, 32×64, 32×16, 16×32, 16×8, 8×16, 8×4 and 4×8.

According To Fig.3 for the data 310 of an image where the resolution is 1920×1080, the size of the maximum coding unit is set to 64×64 and the maximum depth is set to 2.

For data 320 of an image where the resolution is 1920×1080, the size of the maximum coding unit is set to 64×64 and the maximum depth is set to 4. For data 330 of an image where the resolution is 352×288, the size of the maximum coding unit is set as 16×16, and the maximum depth is set to 1.

When the resolution is high or a large amount of data, preferably,but not necessarily, to set the maximum size of the coding unit was relatively large to increase the compression ratio and accurate display characteristics of the image. Accordingly, with respect to data 310 and 320 image with a resolution higher than 330 images, as the size of the maximum coding unit may be selected size 64×64.

The maximum depth indicates the total number of levels in the hierarchical coding units. Since the maximum data depth image 310 is 2, then the unit 315 data encoding image 310 may include a maximum coding unit whose size along the major axis is 64, and subunit encoding whose size in the major axis are 32 and 16, in accordance with increasing depth.

On the other hand, since the maximum data depth 330 image is 1, then the unit 335 data encoding 330 image may include a maximum coding unit whose size along the major axis is 16, and units of coding, which has dimensions on the major axis is 8, in accordance with increasing depth.

However, since the maximum depth of the data image is 320 4, unit 325 data encoding 320 image may include a maximum coding unit, for �otoroy size along the major axis is 64, and subunit encoding, for which the dimensions along the major axis are 32, 16, 8 and 4, in accordance with increasing depth. Because with increasing depth image is encoded based on a smaller subunits encoding, a characteristic variant implementation is applicable for encoding images, comprising the stage with more fine detail.

Fig.4 is a block diagram of the encoder 400 of the image on the basis of the encoding unit in accordance with an exemplary variant of the implementation.

The module 410 internal prediction performs intra prediction on prediction units of the internal mode in the current frame 405, and a module 420, the motion estimation module 425 motion compensation performs mutual prediction and motion compensation on coding units of mutual mode using the current frame 405 and a reference frame 495.

The value of the remainder are formed on the basis of units of predictions issued by the module 410 internal prediction module 420, the motion estimation module 426 motion compensation, and the formed residue values are given as quantized transform coefficients by means of passage through the module 430 conversion module 440 quantization.

Quantized transform coefficients are restored to balance through pass-through module 460 about�atna quantization module 470 inverse frequency conversion, and reconstructed values of the residue subjected to post-processing by passage through the module 480 removal of blockiness and module 490 low-pass filtered and outputted as the reference frame 495. Quantized transform coefficients may be output as a bitstream 455 by passage through an entropy encoder 450.

To perform encoding based on the encoding in accordance with an exemplary variant of implementation of the components of the encoder 400 of the image, i.e., the module 410 internal prediction module 420, the motion estimation module 425 motion compensation module 430 conversion module 440 quantization, entropy encoder 450, the module 460 of the inverse quantization module 470 inverse frequency conversion module 480 removal of blockiness and module 490 low-pass filtering, perform the processes of encoding, based on the maximum unit of encoding subunit coding on the basis of the depths, a prediction unit, and unit conversions.

Fig.5 is a block diagram of the decoder 500 images based on the unit of encoding in accordance with an exemplary variant of the implementation.

Bit stream 505 passes through the module 510 analysis to analyze the encoded image data that must be decoded, and information coding required d�I decode. Encoded image data are given as inversely quantized data by passing through an entropy decoder 520 and the module 530 inverse quantization and restored to balance through pass-through module 540 inverse frequency conversion. The value of balance is restored on the basis of coding units by adding together the result of the internal prediction module 550 internal prediction or motion compensation module 560 motion compensation. Restored the units of encoding are used for predicting the following units of coding or the next frame by means of passage through the module 570 removal of blockiness and module 580 low-pass filtering.

To perform decoding based on the decoding method in accordance with an exemplary variant of implementation of the components of the decoder 500 images, i.e., the module 510 of the analysis, the entropy decoder 520, the module 530 of the inverse quantization module 540 inverse frequency conversion module 550 internal prediction module 560 motion compensation module 570 removal of blockiness and module 580 low-pass filtering, perform the process of decoding images based on the maximum unit of encoding subunit coding based on depth, unit forecast�Oia, and unit conversions.

In particular, the module 550 internal prediction module 560 motion compensation determine a prediction unit and a prediction mode in the subunit encoding, whereas the maximum coding unit and a depth, and the module 540 inverse frequency conversion performs the inverse transformation, taking into account the size of the unit conversion.

Fig.6 illustrates a maximum coding unit, a sub-unit of the coding unit and prediction in accordance with an exemplary variant of the implementation.

The device 100 and device 200 in accordance with an exemplary variant implementation uses a hierarchical encoding unit to perform encoding and decoding, given the characteristics of the image. The maximum coding unit and the maximum depth can adaptively be set in accordance with characteristics of image or variably be set in accordance with the requirements of the user.

The hierarchical structure 600 of coding units in accordance with an exemplary variant of the implementation illustrates the maximum unit 610 encoding, whose height and width is 64 and the maximum depth is 4. The depth increases along the vertical axis of the hierarchical structure 600 of coding units, and with the growth of depth, smart�getting the height and width of subunits from 620 to 650 encoding. The unit of maximum prediction unit 610 encoding the and subunits from 620 to 650 encoding is shown along the horizontal axis of the hierarchical structure 600 of coding units.

Maximum unit 610 encoding has a depth of 0 and the size of the coding unit, i.e. the height and width of size 64×64. The depth increases along the vertical axis, and present: subunit 620 encoding whose size is 32×32 and the depth is equal to 1; subunit of 630 encoding whose size is 16×16 and the depth is equal to 2; subunit of 640 encoding whose size is 8×8 and the depth is equal to 3; and subunit 640 encoding whose size is 4×4 and depth is 4. Subunit 650 encoding whose size is 4×4 and depth is 4 is a minimum coding unit, and the minimum coding unit may be divided into units of predictions, each of which is smaller than a minimum unit of encoding.

According To Fig.6 examples the unit of prediction is shown along the horizontal axis according to each depth. That is, the prediction unit maximum unit 610 encoding, whose depth is 0 may be a prediction unit whose size is equal to the unit 610 encoding, i.e., 64×64, or unit 612 predictions whose size is 64×32, unit 614 predictions, the size of which �leaves 32×64, or unit 616 predictions whose size is 32×32, which have a smaller size unit 610 encoding whose size is 64×64.

Unit of the prediction unit 620 encoding, the depth of which is equal to 1, and the size is 32×32, may be a prediction unit whose size is equal to the unit 620 encoding, i.e., 32×32, or unit 622 predictions whose size is 32×16, unit 624 predictions whose size is 16×32, or unit 626 predictions whose size is 16×16, which have a smaller size unit 620 encoding whose size is 32×32.

Unit prediction unit 630 encoding, the depth of which is equal to 2, and the size is 16×16, may be a prediction unit whose size is equal to one 630 encoding, i.e. 16×16, or unit 632 predictions whose size is 16×8, unit 634 predictions whose size is 8×16, or unit 636 predictions whose size is 8×8, which have a smaller size unit 630 encoding whose size is 16×16.

Unit prediction unit 640 encoding, the depth of which is equal to 3, and the size is 8×8, may be a prediction unit whose size is equal to one 640 encoding, i.e., 8×8, or unit 642 predictions whose size is 8×4, unit 644 predictions, the size of which with�is 4×8, or unit 646 predictions whose size is 4×4, which have a smaller size unit 640 encoding whose size is 8×8.

In conclusion, unit 650 encoding, whose depth is 4 and size is 4×4 is a minimum coding unit and a coding unit of a maximum depth, and the unit of the prediction unit 650 encoding can be unit 650 predictions whose size is 4×4, or unit 652 predictions whose size is 4×2, unit 654 predictions whose size is 2×4, or unit 656 predictions whose size is 2×2.

Fig.7 illustrates the encoding unit and unit conversion in accordance with an exemplary variant of the implementation.

The device 100 and device 200, in accordance with an exemplary variant of implementation performs encoding by means of the maximum unit of encoding or encoding subunits that are equal to or smaller than the maximum coding unit and obtained by splitting the maximum coding unit.

During encoding, the size of the unit for frequency conversion transformation is chosen in such a way as not to be larger than the size of the corresponding coding unit. For example, when the unit 710 encoding has a size of 64×64, frequency transducer.�education can be implemented via unit 720 conversion, having the size of 32×32.

Fig.8A and 8B illustrate a form of division of a coding unit, prediction unit and units conversion in accordance with an exemplary variant of the implementation.

Fig.8A illustrates a coding unit and prediction unit in accordance with an exemplary variant of the implementation.

The left part of Fig.8A shows the shape of the separation, the selected device 100, in accordance with an exemplary variant of the implementation to encode maximum unit 810 coding. The device 100 divides the maximum unit 810 coding on different shapes, performs encoding, and selects the optimal form of separation by comparing the results of the coding of the different forms of separation with each other cost-based R-d optimal When considered the maximum coding unit 810 encoding as it is, then the maximum unit 810 encoding may be encoded without dividing the maximum unit 810 encoding in accordance with what is illustrated in Fig.8A and 8B.

As depicted in the left part of Fig.8A, the maximum unit 810 encoding, the depth of which is equal to 1, coded by means of its division into subunits encoding, the depth of which is equal to or greater than 1. That is, the maximum unit 810 coding is divided into 4 subunit coding, depth Coto�s is 1, and all or some subunit encoding, the depth of which is equal to 1, divided into subunits encoding, the depth of which is equal to 2.

Subunit coding, located in the upper left side, and subunit coding, located in the lower left part, of the subunits encoding, the depth of which is equal to 1, divided into subunits encoding, the depth of which is equal to or greater than 2. Some of the subunits encoding, the depth of which is equal to or greater than 2, can be divided into subunits encoding, the depth of which is equal to or greater than 3.

The right side of Fig.8A shows the shape of the separation units of the predictions for the maximum unit 810 encoding.

As shown in the right part of Fig.8A, the unit 860 predictions for the maximum unit 810 coding may be divided differently than the maximum unit 810 coding. In other words, the prediction unit for each of the subunits encoding may be smaller than the corresponding subunit encoding.

For example, the prediction unit for subunit 854 coding, located in the lower right side, of the subunits encoding, the depth of which is equal to 1, may be smaller subunit 854 coding. In addition, units of predictions for some (814, 816, 850, and 852) of the subunits 814, 816, 818, 828, 850, and 852 encoding, the depth of Kotor�x is 2, can be smaller than the corresponding subunits 814, 816, 850, and 852 of the code. In addition, units of predictions for subunits 822, 832 and 848 encoding, the depth of which is equal to 3, can be smaller than the corresponding subunits 822, 832 and 848 coding. The prediction unit may be in the form from which the corresponding subunit encoding are divided into two equal parts in height or width, or have a shape with which the corresponding subunit encoding are divided into four equal parts in height and width.

Fig.8B illustrates the prediction unit and unit conversion in accordance with an exemplary variant of the implementation.

The left part of Fig.8B shows the shape of the separation units of the predictions for the maximum unit 810 encoding, shown in the right part of Fig.8A, and the right portion of Fig.8B shows the shape of the separation units conversion maximum unit 810 encoding.

As shown in the right part of Fig.8B, the shape of the separation unit 870 conversion can be different from unit 860 predictions.

For example, although the prediction unit for the unit 854 encoding, the depth of which is equal to 1, is selected with a shape whereby the height of the unit 854 coding is divided into two equal parts, the unit conversion can be selected with the same size as the unit 854 coding. Similarly, although the units are pre�legend for units 814 and 850 encoding, the depth of which is 2, is selected with a shape whereby the height of each of the units 814 and 850 encoding is divided into two equal parts, the unit conversion can be selected with the same size as the original size of each of the units 814 and 850 encoding.

Unit conversion can be selected smaller than the unit of prediction. For example, when a prediction unit for unit 852 encoding, the depth of which is 2, is selected with a shape whereby the width of the unit 852 is divided into two equal parts, the unit conversion can be selected with a shape whereby the unit 852 coding is divided into four equal parts in height and width and which has a smaller size than the shape of the prediction unit.

Fig.9 is a block diagram of an apparatus 900 for encoding a picture according to another exemplary variant of the implementation.

According To Fig.9, the device 900 for encoding a picture according to the present exemplary variant implementation includes a module 910, the conversion module 920 quantization and entropy encoder 930.

Module 910 transformation takes the unit of processing image pixel area, and converts the unit of the image processing in frequency domain. Module 910 transformation takes many units of predictions, including the value of the residue formed p�means of internal predictions or mutual prediction and converts the unit of prediction in the frequency domain. As a result of conversion into frequency domain coefficients are formed of frequency components. In accordance with this exemplary variant of implementation of the transformation into frequency domain can occur through discrete cosine transformation (DCT) or the conversion of Caruana-Loeve (KLT), and the resulting DCT or KLT are formed by the coefficients of the frequency domain. Further, the transformation into frequency domain DCT can be, however, a specialist in the relevant field should be obvious that the transformation into frequency domain can be any conversion related to the transformation of the image from the pixel region in frequency domain.

Also in accordance with the present exemplary variant implementation, the module 910 specifies the conversion unit conversion by grouping the plurality of prediction units and performs the conversion in accordance with unit conversion. This process will be described with reference to Fig.10, 11A, 11B and 12.

Fig.10 is a diagram of the module 910 of the conversion.

According To Fig.10 module 910 transformation includes a module 1010 of choice and a module 1020 perform the conversion.

Module 1010 of choice defines the unit of conversion by selecting multiple adjacent units p�of eskasoni.

Encoding device image in accordance with a related technical field, performs intra prediction or mutual prediction on the basis of a block having a predetermined size, i.e. on the basis of the prediction unit, and performs DCT on the basis of size, which is less than or equal to a given unit of prediction. In other words, the encoding device image in accordance with a related technical field, performs DCT using conversion units which is less than or equal to one prediction.

However, because of the many parts of the header information that is added to the units conversion, incremental overhead grows with decreasing conversion units, thereby deteriorating the degree of compression encoding of the image. In order to solve this problem, the device 900 for encoding a picture according to the present exemplary variant implementation groups the set of neighboring prediction units in unit conversion and performs the conversion in accordance with the unit of conversion, which is formed by the grouping. There is a high probability that the neighboring prediction unit may include the same values of balance, and thus, if the neighboring prediction unit are grouped into a unit change�hardware and then over them converted it can be greatly increased compression ratio encoding.

For this zoom module 1010 selects the neighboring prediction unit that will be grouped in unit conversion. This process will be described with reference to Fig.11A-11C and 12.

Fig.11A-11C illustrate the types of units conversion in accordance with another exemplary variant of the implementation.

According To Fig.11A-11C unit 1120 predictions for unit 1110 coding may be in the form of division obtained by dividing in half width units 1110 coding. Unit 1110 coding can be a maximum coding unit or may be a subunit of a coding amount is less than the maximum unit of encoding.

As illustrated in Fig.11A, the size of the unit 1130 conversion may be less than unity 1120 predictions, or, as illustrated in Fig.11B, the size of the unit 1140 predictions can be equal to unit 1120 predictions. Also, as illustrated in Fig.11C, the size of the unit 1150 transformation may be more units 1120 predictions. That is, units from 1130 to 1150 transformation can be established without reference to unit 1120 predictions.

Fig.11C illustrates an example in which unit 1120 predictions set by grouping the plurality of units of 1120 preska�ing, included in unit 1110 coding. However, the unit conversion can be set greater than the coding unit, a prediction units that are not included in one coding unit, and many units of encoding are installed as one unit conversion. In other words, as described with reference to Fig.11A-11C, the unit conversion can be set equal to or smaller than the size of the unit of coding, or greater than the size of the unit of coding. That is, the unit conversion can be specified without reference to the prediction unit and the encoding unit.

Although Fig.11A-11C illustrate examples in which translation units has a square shape, however, in accordance with the method of grouping neighboring prediction units unit conversions may have a rectangular shape. For example, in the case where the prediction unit is not specified as having a rectangular shape, as illustrated in Fig.11A-11C, and is defined as having four square form obtained by division into four parts unit 1110 encoding, the upper and lower units of the prediction or the left and right units predictions are grouped in such a way that the unit conversion may be a rectangle whose horizontal side or the vertical side is longer.

With reference to Fig.10, there are no restrictions on the criterion on the basis of which the module 1010 select selects the neighboring prediction units. However, in accordance with an exemplary variant of implementation of the module 1010 of choice can make the selection unit conversions on the basis of depth. As described above, the depth indicates the degree of size reduction that occurs gradually from the maximum coding unit of the current macroblock or sequence of the current frame to the subunit encoding. As described above with reference to Fig.3 and 6, as the depth decreases the size of the subunit encoding and consequently also decreases the prediction unit included in the subunit encoding. In this case, if the conversion is performed in accordance with the unit of conversion, which is less than or equal to one prediction, the degree of compression encoding of the image deteriorates, because each unit of the conversion is added to the header information.

Thus, with respect to the subunit encoding at a depth corresponding to a predetermined value, preferably, but not necessarily to the prediction unit included in the subunit encoding, grouped and asked as unit conversion and then played over her�axis transformation. For this module 1010 of choice defines the unit of conversion on the basis of depth subunit coding. For example, in the case where the depth unit 1110 coding in Fig.11C is greater than k, the module 1010 select groups of units 1120 predictions and sets them as the unit 1150 of the conversion.

In accordance with another exemplary variant of implementation of the module 1010 can select to group the set of neighboring prediction units on which prediction is performed according to the same prediction mode, and can set them as single units conversion. Module 1010 select groups of neighboring prediction unit on which prediction is performed based on internal predictions or mutual prediction, and then sets them as one unit conversion. Since there is a high probability that the neighboring prediction unit on which prediction is performed according to the same prediction mode, include the same value of the residue, it is possible to group the neighboring prediction unit in the unit of conversion, and then perform the transform over the neighboring prediction units.

When the selection module 101 defines the unit of conversion, the module 1020 conversions, converts the neighboring prediction unit � frequency region in accordance with unit conversion. Module 1020 conversions, performs DCT on neighboring units conversion in accordance with unit conversion and generates a discrete cosine coefficients.

According To Fig.9 module 920 quantization quantum the coefficients of the frequency components generated by module 910 transformation, such as discrete cosine coefficients. Module 920 quantization to quantize the discrete-cosine coefficients, which are introduced in accordance with a predetermined quantization step.

Entropy encoder 930 performs entropy encoding of the coefficients of the frequency components quantized by the module 920 quantization. Entropy encoder 930 may perform entropy encoding on discrete cosine coefficients through the use of context-based adaptive variable arithmetic coding (CABAC) or context-dependent adaptive coding with variable length (CAVLC).

The device 900 for encoding a picture can determine the best unit conversion via repetitive perform DCT, quantization and entropy coding on different units conversion. To determine the optimal unit conversion the process of selecting a neighboring prediction units may be repeated. Optimal unit conversion�tion can be determined, whereas the computation of RD cost, as described in detail with reference to Fig.12.

Fig.12 illustrates different units conversion in accordance with another exemplary variant of the implementation.

According To Fig.12, the device 900 for encoding a picture repeatedly performs the encoding operation over the different units of the conversion.

As illustrated in Fig.12, unit 1210 coding can predskazivati and encoded based on unit 1220 predictions, having a smaller size than unit 1210 coding. The conversion is performed on the values of the residues, which are formed by the result of the prediction, and here, as illustrated by Fig.12, the DCT may be performed on residue values based on different units conversion.

First illustrated unit 1230 conversion has the same size, and unit 1210 coding, and it has a size obtained by grouping all the prediction units included in unit 1210 encoding.

The second illustrated unit 1240 conversion has a size obtained by dividing in half width unit 1210 encoding, and the sizes obtained by grouping every two prediction units adjacent to each other in the vertical direction, respectively.

The third unit illustrated 1250 pre�fatality has dimensions, obtained by dividing in half height unit 1210 encoding, and the sizes obtained by grouping every two prediction units adjacent to each other in the horizontal direction, respectively.

Fourth illustrated unit 1260 conversion is used when the conversion is done on the basis of the fourth unit illustrated 1260 conversion having the same size as unit 1220 predictions.

Fig.13 is a block diagram of an apparatus 1300 decoding image in accordance with another exemplary variant of the implementation.

According To Fig.13, the device 1300 decoding image in accordance with the present exemplary variant implementation includes an entropy decoder 1310, a module 1320 inverse quantization module 1330 return convert.

Entropy decoder 1310 performs entropy decoding on the coefficients of frequency components on a predetermined unit conversions. As described above with reference to Fig.11A-11C and 12, a predetermined unit conversion can be a unit conversion information generated by grouping a plurality of adjacent prediction units.

As described above with reference to the device 900 image encoding unit conversion can� to be formed by grouping neighboring prediction units based on the depth or may be formed by grouping the plurality of adjacent prediction units, over which prediction is performed according to the same prediction mode, that is, in accordance with the mode of internal predictions or mode of mutual prediction.

Many units of the predictions may not be included in one coding unit and included in many units of encoding. In other words, as described above with reference to Fig.11A-11C, unit conversion, which is entropy decoded by entropy decoder 1310, may be set as equal to or less than the size of the unit of coding, or larger than the size of the unit of encoding.

As described above with reference to Fig.12, the unit conversion may be the best unit conversion, selected by repeating the procedure of grouping the plurality of adjacent prediction units, and through repeated execution of the transform, quantization and entropy decoding on the different units of the conversion.

Module 1320 inverse quantization returning quantum the coefficients of the frequency components, which are entropy-decoded entropy decoder 1310.

Module 1320 inverse quantization returning quantum entropy decoded coefficients of the frequency components in accordance with the quantization step used for encoding units conversion.

Module 1330 reverse�CSO conversion performs the inverse transform is inversely quantized coefficients of the frequency components in the pixel region. The inverse transformation module may perform the inverse-DCT on inversely quantized discrete cosine coefficients (i.e., inversely quantized coefficients (frequency components) and can then recreate the unit conversion in the pixel region. Recreated unit conversion may include neighboring prediction unit.

Fig.14 is a block diagram of the sequence of operations of a method of encoding an image according to an exemplary variant of the implementation.

According To Fig.14, in operation 1410, the device image encoding unit sets the conversion by selecting the plurality of adjacent prediction units. Encoding device of the image may select a set of neighboring prediction units in accordance with the depth or may select a set of neighboring prediction units on which prediction is performed according to the same prediction mode.

In operation 1420, the device image encoding converts the neighboring prediction unit into frequency domain in accordance with unit conversion, set in operation 1420. Encoding device of the image groups of the neighboring prediction unit, performs the DCT over the neighboring prediction units and thus forms a discrete cosine coefficient�.

In operation 1430, the device image encoding quantum the coefficients of the frequency components generated in operation 1420, in accordance with the quantization step.

In operation 1440, the device image encoding performs entropy encoding on the coefficients of the frequency components quantized in operation 1430. The device image encoding performs entropy encoding on discrete cosine coefficients using CABAC or CAVLC.

The method of encoding images in accordance with another exemplary variant implementation may further include an operation for setting the optimal units conversion via repetitive operations 1410-1440 on different units conversion. That is, through repeated execution of the transform, quantization and entropy coding on different units conversion, as illustrated in Fig.12, it is possible to establish the optimal unit conversion.

Fig.15 is a block diagram of the sequence of operations of a method of decoding images in accordance with another exemplary variant of the implementation.

According To Fig.15, in operation 1510, the decoding device performs image entropy decoding on the frequency coefficients sostavlyajushie� in relation to a pre-defined unit conversion. The coefficients of the frequency components may be discrete cosine coefficients.

In operation 1520, the device decoding the image back quantum the coefficients of the frequency components, which are entropy decoded in operation 1510. The decoding device image back quantum discrete cosine coefficients by using a quantization step used for encoding.

In operation 1530, the decoding device image is inversely transforms the coefficients of the frequency components that were inversely quantized in operation 1520, in the pixel region and then recreates the unit conversion. Recreated unit conversion is set by grouping the plurality of adjacent prediction units. As described above, the unit conversion can be specified by grouping neighboring prediction units based on the depth or may be set by grouping the plurality of adjacent prediction units, a prediction which is performed according to the same prediction mode.

In accordance with one or more exemplary variants of implementation it is possible to set units conversion so that it was larger than the unit of prediction and the DCT so that the image�tion may be effectively compressed and encoded.

Exemplary embodiments of the implementation can also be embodied as computer readable codes on a computer-readable recording media. The computer-readable recording medium is any data storage device that can store data which can later be read by a computer system. Examples of computer readable recording media include read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tapes, floppy disks and optical storage devices. The computer-readable recording medium can also be distributed among networked computer systems so that the computer readable code is stored and executed in a distributed manner.

For example, each of the device image encoding device, image decoding, image encoder and image decoder in accordance with one or more variants of implementation may include the bus associated with each module in the device, as illustrated in Fig.1-2, 4-5, 9-10 and 14, and at least one processor associated with the tire. Each of the device image encoding device, image decoding, image encoder and image decoder in accordance with one or more variants of implementation may include a memory associated with at least one processor, �which is associated with the tire, to store commands, received messages, or generated messages and executing commands.

Although the present invention is shown and described in detail with reference to its exemplary implementation options, specialists in the relevant field should be clear that with regard to him can be made various changes in form and detail without departing from the essence and scope of the invention as defined by the appended claims of the invention. Exemplary embodiments of the implementation should be considered only in an explanatory sense, and not for the purpose of imposing restrictions. As such, the scope of the invention is defined not by the detailed description of the invention and the appended claims, and all differences lying within the volume shall be considered as included in the present invention.

1. Method of decoding image containing phases in which
define the hierarchical structure of coding unit for decoding the image, at least one prediction unit for predicting each of the coding units and at least one unit of conversion for inverse transforming each of the coding units by using information about the shape of dividing the coding unit, information about at least one prediction unit and and�formation of at least one unit of conversion, obtained through analysis from a received bitstream of an encoded video;
obtained by analysis from the bitstream transformation coefficients generated by transformation in accordance with at least one unit of transformation generated by dividing the coding unit, and restores the encoded data at least one prediction unit by performing entropy decoding, inverse quantization and inverse transformation on the obtained by analyzing the transform coefficients; and
perform intra prediction or mutual prediction over the restored coded data and restore the encoded video,
the units of encoding are separated hierarchically in accordance with the depth units of coding, and
at least one unit of the conversion unit contains transform having a size different from the size of at least one unit of the predictions.

2. A method according to claim 1, wherein at least one prediction unit contains many units of predictions and
wherein at least one unit of the conversion unit contains conversion that is larger than the size of a plurality of prediction units.

3. A method according to claim 1, wherein the size of at IU�e one unit of conversion differs from the size of the at least one prediction unit and the size of the unit of encoding.

4. A method according to claim 1, wherein the video coded video coded on the basis of information about the maximum size of a coding unit and a depth units of coding, in which the coding unit is hierarchically split into units of coding depth of coding according to the depths
the coding unit of a current depth is one of rectangular data units obtained by the division of the units of encoding higher depth, and
in this case, the coding unit of the current depth is split into units of coding a lower depth up to coding units corresponding to depths of the coding independently from neighboring coding units.



 

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13 cl, 2 dwg

FIELD: physics, computer engineering.

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9 cl, 6 dwg

FIELD: physics, video.

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28 cl, 13 dwg

FIELD: physics, computer engineering.

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10 cl, 4 dwg, 1 tbl

FIELD: physics, communications.

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7 cl, 5 dwg

FIELD: physics, computer engineering.

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63 cl, 6 dwg

FIELD: physics, video.

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2 cl, 21 dwg, 3 tbl

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24 cl, 15 dwg

FIELD: physics, video.

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13 cl, 4 dwg

Brightness meter // 2549605

FIELD: instrumentation.

SUBSTANCE: brightness meter contains an opaque light filter attached to a piezoelectric element which is connected to a frequency divider output, a lens, a pyramidal mirror octahedron with four external smooth surfaces and four disk photodetectors, each with two photoreception sectors. Photoreception sectors are fitted with colour light filters. The output of each photoreception sector is connected to the input of an analogue-digital converter. Each analogue-digital converter comprises the pulse amplifier to the output of which pulse light-emitting diodes are connected. Radiation from each light-emitting diode enters the group of eight identical photodetectors, each of which has on the reception side a neutral light filter with a ratio respectively of the register digit weight to which the output of each photodetector is connected.

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2 dwg, 1 tbl

FIELD: physics, computer engineering.

SUBSTANCE: invention relates to image compression systems and methods. The method of compressing a digital image in a computing device comprises steps of dividing an image into a plurality of image subregions; selecting from a catalogue which includes a plurality of predetermined template forms, wherein each template form comprises a plurality of elements, properties and image variables, such as colour, colour gradient, gradient direction or reference pixel, and wherein each said form is identified by a code, the template form of each subregion best corresponding to one or more image elements of said subregion; and generating a compressed data set for the image, wherein each subregion is represented by a code which identifies the template form selected therefor.

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22 cl, 4 dwg

FIELD: physics.

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FIELD: physics, photography.

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19 cl, 26 dwg

FIELD: information technology.

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3 dwg

FIELD: physics.

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EFFECT: reduced cross dimensions of array elements in an image sensor, which enables to reduce the frame format size or increase resolution of the image sensor.

6 dwg, 1 tbl

FIELD: physics.

SUBSTANCE: disclosed is a frame image digitisation apparatus. The disclosed apparatus comprises a lens in the focal plane of which there is an image sensor having an array of elements, a control signal generator and three register units, the outputs of which are the outputs of the digitisation apparatus. Each array element consists of a converter for converting radiation of colours R, G, B into three codes. Images are input into the sensor, the number of said images being equal to the number of array elements and the number of colours R, G, B of analogue-to-digital converters (ADC).

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4 dwg, 2 tbl

FIELD: physics.

SUBSTANCE: apparatus comprises a lens, an image detector having an array situated in the focal plane of the lens, the array having elements which are converters for converting radiation to codes based on the frame resolution number 106, each having an opaque housing in the front part of which, in a partition wall, there is a microlens, on the optical axis of which and at an angle of 45° thereto semitransparent micromirrors are arranged in series and rigidly mounted based on the number of bits per code, each preceding micromirror transmitting to the next micromirror radiation flux with half the strength.

EFFECT: high speed of frame digitisation.

1 tbl, 4 dwg

FIELD: physics.

SUBSTANCE: apparatus comprises a lens, an image detector which includes an array of elements based on the frame resolution number 106, situated in the focal plane of the lens and having three groups of outputs of colour codes R, G, B, includes three register units and a control signal generator which outputs from the first output pulses with frame frequency (25 Hz), connected to the control inputs in array elements, and from the second output pulses with code sampling frequency, connected in parallel to the second control inputs of the first through third register units.

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5 dwg, 1 tbl

FIELD: information technology.

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EFFECT: higher productivity of an electronic documents contensive processing system and increase in the analysed data sources number.

5 dwg

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