# Coding elementary-wave data by means of null tree

**FIELD: coding elementary-wave data by means of null tree.**

**SUBSTANCE: proposed method includes generation of elementary-wave ratios pointing to image. In the process bits of each elementary-wave ratio are associated with different bit places so that each place is associated with one of bits of each elementary-wave ratio and associated bits are coded with respect to each place of bits to point to null tree roots. Each place of bits is also associated only with one of bits of each elementary-wave ratio. Computer system 100 for coding elementary-wave ratios by means of null tree has processor 112 and memory 118 saving program that enables processor 112 to generate elementary-wave ratios pointing to image. Processor 112 functions to code bits of each place to point to null tree roots associated with place of bits.**

**EFFECT: enhanced data compression speed.**

**18 cl, 7 dwg**

The scope and level of technology to which the invention relates.

The invention relates generally to coding using zero-tree data elementary waves, such as coding using zero trees coefficients of elementary waves.

Data compression is usually removes redundant information from the data series for the formation of another series data having a smaller size. This smaller size may be preferable, for example, for the purposes of data transfer through a bus or network.

For example, the intensity of the picture elements can be specified using a number of coefficients, and these coefficients can be represented by digital image data. The purpose of data compression of image data can be transformed to identify redundant information, i.e. information can be removed by using data compression. For example, image data may be converted by the conversion of elementary waves in the spatial filtered image called frequency sub-bands. Thus, the sub-bands can reveal a significant amount of redundant information, which can be removed by using compression technology.

As shown in figure 1 as an example, image data, which indicate the intensity of the elements of the original image 12 evaluation of the bending transformations of elementary waves for dividing the image 12 on the subranges. Due to the nature of the transformation sub-bands appear at different levels of decomposition (e.g., at levels 14, 16 and 18). Thus, for a decomposition of the original image 12 on the sub-bands 14a, 14b, 14C and 14d of the first level 14 decomposition applies a one-dimensional discrete transform of elementary waves (DWT) to the rows and columns. When the one-dimensional discrete transform of elementary waves of the signal (e.g., line) is first passed through a low pass filter and subjected to podcantario by lowering alternating filtered output signal to generate low-frequency subband (L), which is half the size of the original signal. Then the same signal is passed through high-pass filter and subjected to the same podcantario to create a high-frequency subband (N), which is half the size of the original signal. When the same one-dimensional operation applied to the columns in the sub-band L, then create two sub-bands LL and LH. Similarly, applying the same one-dimensional operation to the columns in the LH sub-band, create two sub-bands HL, and HH. As a result, when the two-dimensional transform of elementary waves of the original image is decomposed into four sub-bands: LL sub-band 14a, LH sub-band 14b, HL sub-band 14C and low voltage sub-range 14d. The size of the string and the hundred and the GCA of each of these sub-bands is equal to half the size of the row and column of the original image due to the operation podkashivaya. The values of these sub-bands are called the coefficients of elementary waves and therefore the sub-bands can be represented in the form of a corresponding matrix of coefficients of elementary waves.

The LL sub-band 14a indicates the low-frequency information in both the horizontal and vertical directions of the image 12 and is usually a considerable amount of information present in the image 12, because it is nothing more than podkastany version of the original image 12. LH sub-band 14b indicates the low-frequency information in the horizontal direction and high frequency information in the vertical direction, i.e. the information of the horizontal path. HL sub-band 14C indicates the high-frequency information in the horizontal direction and low frequency information in the vertical direction, i.e. the vertical contour information. NN subrange 14d indicates high-frequency information in the horizontal direction and high frequency information in the vertical direction, i.e. information diagonal path.

Since the LL sub-band 14a is nothing more than podkastany version of the original image, it retains the spatial characteristics of the original image. In the same decomposition using the transform of elementary waves can be applied on the additional to obtain four sub-bands, which have half the resolution of the LL sub-band 14a both in vertical and in horizontal directions: the LL sub-band 16A, LH sub-band 16b, HL sub-band 16C and low voltage sub-range 16d. Thus, the LL sub-band 16A is again podkastany version of the LL sub-band 14a. The LL sub-band 16A can be further decomposed into four sub-bands, which are half the size of its resolution in both the horizontal and vertical directions: LL sub-band 18a, LH sub-band 18b, HL sub-band 18C and low voltage sub-range 18d.

Sub-bands of lower levels of decomposition point information in the original image 12 in smaller parts (i.e. sub-bands indicate the version with a higher resolution image 12)than the corresponding sub-bands of higher levels of decomposition. For example, low-voltage sub-range 18d (the ancestor of the HH subband 16d) specifies the information that is present in the original image 12 in coarser detail than NN subrange 16d (a descendant of the HH subband 18d), and low voltage sub-range 14d (another descendant of the HH subband 18d) image indicates information that is present in the original image 12 in more fine detail than the HH sub-bands, 16d and 18d. Thus, the position of the 24 item image HH subband 18d image complies with the provisions 22 of the four elements is s image HH subband 16d and sixteen provisions 20 HH subband 14d.

Due to the relationship of the positions of the picture elements between the parent sub-band and its descendants, you can use a technique called zero coding tree for the identification of the coefficients of elementary waves, called zero roots of the tree. In General, the zero root of the tree is the coefficient of elementary waves, which satisfies two conditions: the coefficient has negligible intensity, and all descendants of the coefficient are negligible intensity relative to a certain threshold. Thus, thanks to this relationship, the chain insignificant coefficients can be specified using a single code, which is a compression size of the data, which indicates the original image. For example, if the ratio of elementary waves for position 24 is zero root of the tree, the coefficients of elementary waves for locations 20, 22 and 24 are minor and can be described by a single code.

Encoding each level of decomposition usually consists of two passes: the dominant pass to determine the dominant list of coefficients of elementary waves, which are assessed as minor, and a downstream passage for determining the subordinate list of coefficients of elementary waves, which is defined as the e significant. During the sub-passage can be calculated threshold for each subband and used to assess whether the coefficients of the subband minor or major. Unfortunately, due to the complexity of the calculations described above compression technology may be too slow for some applications, such as applications to compress interactive video.

Thus, there is a continuing need in the system, which allows to solve one or more of the above problems.

The invention

In one embodiment, the method includes obtaining coefficients of elementary waves, which indicate the image, and predstavleniya each coefficient of elementary waves in the form of a set of ordered bits.

Advantages and other features of the invention follow from the subsequent description, drawings and claims.

Brief description of drawings

In the drawings shows:

figure 1 - hierarchical order of sub-bands generated by converting the elementary waves;

figure 2 - block diagram of a computer system, according to a variant implementation of the invention;

figure 3 - the scan path to determine the zero roots of the tree, according to a variant implementation of the invention;

figure 4 - organization of the matrix of coefficients elem is nternal waves, according to a variant implementation of the invention;

5 is a scan path for the matrix of coefficients of elementary waves;

6 - the path to locate the position of the zero roots of the tree;

7 is a graphical diagram of the execution of the program to encode the coefficients of elementary waves, according to a variant implementation of the invention.

Detailed description

As shown in figure 2, a variant program execution 119 compression, according to this invention, can provide a by-bit encoding processor 112 coefficients of elementary waves. Thus, instead of classifying factors of the elementary waves (for example, zero roots of a tree or isolated zeros), the processor 112 can generate codes for classification of the bits of the coefficients of elementary waves. For example, in some embodiments, execution of the processor 112 may classify specific bits as zero root of the tree, isolated zero, positive, node negative or node. Unlike conventional encoding schemes zero tree, the threshold values are not calculated to identify small quantities because the bit "0" is treated as insignificant, and the bits of "-1" and "1" are treated as significant bits.

Thus, the processor 112 may create for the classification of specific bits of one of the following is x code: code P to indicate a positive node, if the bit indicates "1"; code N to indicate a negative node, if the bit indicates "-1"; code R to indicate that the bit "0" is a zero root of the tree; and code IZ to indicate that the bit is "0" is an isolated zero. According to other variants of execution of the invention, the specific bit is classified as a negative node, only if the bit is the most significant non-zero bit and the bit indicates "-1". For example, for the factor "-3", which is represented by three bits "-011", the CPU 112 generates code N to represent the middle bit. However, for example, the processor 112 generates code P to represent the least significant bits.

To create coefficients of elementary waves of the processor 112 may use transformations of elementary waves to decompose the coefficients that represent the intensity of the elements of the original image. These factors of the elementary wave form, in turn, sub-bands, which are located in several levels of decomposition. For classification bits processor 112 may, in some versions to run the program 119 for processing bits on the basis of their relevant provision or discharge of bits. Thus, the bits of each digit of bits in a hierarchical tree that can bypass the processor 112 to classify bits of wood as to the nya zero tree isolated zero, negative, node positive or node. Thus, for example, the most significant bits of the coefficients of elementary waves (this bit may be zero) associated with one hierarchical tree (and one discharge bits), and the next most significant bits associated with other hierarchical tree (and other discharge bits).

For example, if absolutely maximum coefficient of elementary waves is represented by three bits (as an example), then all the coefficients of elementary waves should be represented by three bits. So in this example there are three hierarchical tree. Thus, the processor 112 generates code for each bit on the basis of the indicated value (i.e. "-1", "0" or "1") and possibly (if the bit indicates "0"), its position in the corresponding hierarchical tree.

According to some variants of execution of the processor 112 indicates codes R, N, or R IZ using a stream of bits, which is consistent over time indicates a more detailed (i.e., higher resolution) version of the original image. For example, the processor 112 may use the bits "00" to indicate code R, the bits "01" to indicate code N bits of "10" to indicate code R and the bits "11" to indicate code IZ. Other encoding schemes. The sequential nature of the bit stream is characterized by the for the order, in which the processor 112 processes the discharge of bits. For example, in some embodiments, execution of the processor 112 may process the bits of the bits in the processing mode, first the most significant. Therefore, the process 112 may first generate code for all the bits that have the highest level of bits, then create the code for all the bits having the next highest category bits, etc. as a result of this sequential encoding of the resulting bit stream may first specify a coarser version of the original image. Over time, however, the bit stream indicates more of the subtleties of the image as the processor 112 generates codes for bits with lower rank bits. Thus, in some embodiments, execution of the resolution of the image specified by the bit stream, improves with time, which is a desirable characteristic for systems with limited bandwidth. By reducing the resolution of the reconstructed image can be provided by reducing the width of the band.

As shown in figure 3, in some embodiments, execution of the processor 112 processes the bits of each digit in sequence. For example, for a particular discharge bits processor 112 may begin with the highest level of decomposition and create codes for bits of the higher level decomposed the I before moving on to the creation of codes for the next higher level of decomposition. The processor 112 generates code (codes) for a bit (bits) sub-bands LL and then for each level of decomposition generates code (codes) for a bit (bits) sub-bands LH, and then generates code (codes) for a bit (bits) sub-bands HL, and finally generates code (codes) for a bit (bits) sub-band LV.

As an example, the coefficients of elementary waves generated by two-level decomposition, can be placed in the matrix 40, shown in figure 4. Thus, the matrix 40 may be considered as divided into four quadrants 30A, 30b, 30C and 30d. The upper right quadrant 30b, the lower left quadrant 30C and the lower right quadrant 30d contain the coefficients for the image of the sub-bands LH, HL and HH, respectively, the first level of decomposition. The coefficients for the image of the sub-bands LL, LH, HL and HH of the second level of decomposition are located in the upper right quadrant 32A, the upper right quadrant 32b, the lower left quadrant 32C and the lower right quadrant 32d of the upper-left quadrant 30A. The coefficients generated using the optional decomposition can be located similarly. For example, for the third level of decomposition of the upper-left quadrant 32A contains the coefficients of the elementary wave of sub-bands LL, LH, HL and HH of the third level of decomposition.

If the matrix of coefficients, which indicates the intensity of the elements in the original image is to be placed, is the matrix 4×4, the matrix 40 may take the form shown in figure 5. Thus, the image of the sub-bands LL, LH, HL and HH of the second level of decomposition have every single factor, represented by "A" (for image subband LL), "" (for image subband LH), "C" (for image subband HL) and "D" (for image subband HH), respectively. As shown in figure 5, for the first level of decomposition coefficients for the image of the sub-bands LH, HL and HH presents the following relevant matrices:

It should be noted that each coefficient of the second level of decomposition (except A) associated with at least four coefficients of the first level of decomposition, i.e. each coefficient of the first level of decomposition has at least four children coefficient (descendant) at the second level of decomposition. Therefore, each bit in the first level of decomposition has at least four child ratio at the second level of decomposition.

For each digit bits processor 112 may process the bits in the scan sequence described above. If a particular bit indicates "1" or "-1", then the processor 112 generates code P or N and proceeds to the next bit in the scan sequence. However, if a particular bit is found "0", the processor 112 can monitor the bit through his descendants to determine whether the bit isolated zero zero or root of the tree. The coefficients in the LL sub-band are simply coded unordered.

For example, to generate code for the least significant bits (called D(1)) factor D (located in the sub-range NN second level decomposition), the processor 112 determines if D(1) "0". If Yes, then the processor 112 evaluates the child bits G1(1)G2(1), G3(1) and G4(1) of the HH subband of the first level of decomposition in search of "1" or "-1"as shown in Fig.6. If one of these bits indicates "1" or "-1", then D(1) is an isolated zero. Otherwise, D(1) is the zero root of the tree.

As a digital sample matrix 4×4 coefficients, which indicates the intensity of the picture elements may be subjected to a two-level decomposition for the formation of the following matrix:

Since the maximum absolute value is "4", you can use three bits to represent the coefficients, as shown in the following matrix:

Therefore, the CPU 112 starts encoding to generate codes for bits of the third category (i.e. the most significant bits, which can also be zero) coefficie the tov. In particular, to generate code bits of the third discharge processor 112 by 28 (see figure 5) and generates the appropriate code for the third bit of each coefficient along the path 28. If a particular bit indicates "0", the processor 112 evaluates descendants bit to find isolated zeros or zero roots of the tree. The encoding of bits of the third discharge processor 112 leads to the creation of the following codes (listed in order of creation): P, R, R, R Then the processor 112 generates codes for bits in the second category (listed in order of creation): IZ, IZ, N, R, IZ, P, IZ, IZ, IZ, P, IZ, IZ. Finally, the processor 112 generates codes for bits of the first category (listed in order of creation): IZ, P, IZ, R, P, IZ, IZ, P, IZ, P, IZ, P. As mentioned above, the processor 112 can enter the codes using the schema dobitogo encode and transmit the codes, as they are created, using the bit stream.

As another example, the processor 200 (see figure 2) can use the bit stream to reconstruct the matrix of coefficients, which indicates the intensity of the elements of the original image, as follows. Before decoding, the processor 200 first receives from the processor 112 indicating that it was used three levels of coding (i.e. one level for each digit in bits). After receiving this information, the processor 200 can reconstruire the th original matrix coefficients using the codes in the sequence, which was created codes. In particular, the processor 200 may use codes generated by encoding the bits of the third category (i.e. the first level of coding) to create the following matrix:

The processor 200 may use this matrix to reconstruct a rough version (i.e. the version with low resolution) of the original image. However, if desired refined version, the processor 200 can use the codes that are generated by encoding the bits in the second category (i.e. the second level of coding) to create the following matrix:

Finally, if the processor 200 uses codes that are generated by encoding the bits of the first digit (i.e. the third level of coding), the CPU 200 generates source matrix decomposed coefficients of elementary waves.

As shown in Fig.7. as a result, the program 119 compression, when executed by processor 112, can ensure that the process 112 the following procedure to implement the above coding. First, the CPU 112 outputs (stage 72) matrix decomposed coefficients shown in binary form. Then, the controller 112 determines (stage 74) the number of digits needed to represent the absolute value of the maximum coefficient of elementary waves. Getprocessor 112 uses a variable (called n), which indicates the current discharge of bits processed by the processor 112. Thus, the processor 112 uses the cycle software for processing sequentially the bits of one bit. To accomplish this, the processor 112 generates codes (stage 76) bits for the current category using the above technologies. Then, the controller 112 determines (stage 78)whether the speed of bits to exceed the bit rate. If Yes, then the processor 112 completes the encoding of the current image to fit a given bit rate. Otherwise, the processor 112 determines (stage 80), processed if all the bits of the bits, i.e., the processor 112 determines is equal to n? "1". If not, the processor 112 reduces per unit (stage 75) discharge, which indicates the variable n, and proceeds to the step 76 for the passage of the loop once more to create codes for bits other bits. Otherwise, the encoding is finished.

As shown in figure 2, in some embodiments, execution of the processor 112 may be part of computer system 100. A computer system may include a gateway or hub 116 of the memory, and the processor 112 and the hub 116 of the memory can be connected to the bus 114 of the host computer. The hub 116 of the memory provides interfaces for connecting together bus 114 of the host computer bus 129 memory isini 111 high-speed graphics port (AGP). High-speed graphics port described in detail in the Accelerated Graphics Port Interface Specification, Revision 1.0, published on July 31, 1996 the company Intel Corporation of Santa Clara, California. System memory 118 may be connected to the memory bus 129 and store program 119 compression. As mentioned above, the program 119 compression when executed by processor 112 provides for the establishment by the processor 112 of the coefficients of elementary waves, which indicate the image, and the representation of each coefficient of elementary waves in the form of a set of ordered bits. The processor 112 encodes the bits of each digit to indicate zero roots of the tree that are associated with the category.

Other signs of a computer system 100 includes connection controller 113 of the display (which controls the display 114) bus 111 high-speed graphics port. The communication line 115 of the hub can connect the hub 116 of the memory with another gateway loop, or hub 120 input/output. In some embodiments, performing the hub 120 I/o can contain interfaces to the bus 125 expansion I/o and bus 121 peripherals (PCI). Description PCI can be obtained from the company The PCI Special Interest Group, Portland, Oregon 97214.

Bus 121 PCI, leading to the telephone line 142 may be connected to the modem 140. Thus, the modem 140 may provide an interface that provides lane is giving a stream of bits, created by the processor 112, the processor 200. The hub 120 I/o may also contain interfaces, for example, to the actuator 132 of the hard disk and to the actuator 133 CD-ROM. Bus 125 expansion I/o can be connected to the controller 117 I/o, which receives input data, such as from a keyboard 124, mouse 126. The controller 117 I/o may also control the operation of the actuator 122 floppy. Copies of the program 119 may be stored, for example, the actuator 132 hard disk, diskette, or CD-ROM, as some examples.

In the context of this application, the terms "computer system" may refer generally to based on the processor system, and may include (but not limited to) graphics system, a desktop computer or a portable computer (for example, a compact portable computer), as some examples. The term "processor" may include, for example, by the microcontroller, microprocessor, X86, ARM microprocessor (chip with a reduced instruction set), a microprocessor-based Pentium. The above examples are not restrictive, and in versions of the invention can use other types of computer systems and other types of processors.

Other embodiments of the inside volume of the subsequent claims. For example, matrix resoundingfinale, described above have one coefficient in each sub-band of the highest level of decomposition. However, this system is provided only to facilitate describing the encoding. Therefore, each sub-band of the highest level of decomposition can be many factors and the above technology can be used to encode the bits associated with these factors. In some embodiments, execution of the processor 112 can encode in parallel all of the bits of each digit. Thus, the encoding of the bits of each digit of bits can be performed by the processor is executing a separate subprocess. Alternative.

Although the invention is disclosed as applied to a small number of embodiments, for specialists in this field of technology understandable numerous modifications and variations on the basis of this disclosure. It is assumed that the dependent claims cover all these modifications and variations, as appropriate to the idea and scope of the invention.

1. The encoding method using the zero-tree coefficients of elementary waves, contains the creation of the coefficients of elementary waves, which indicate the image, while the bits of each coefficient of elementary waves associated with various bits bits so that each digit bits of the AC which Ochirova with one of the bits of each coefficient of elementary waves and in relation to each of the bits of the bit encoding of the associated bits to specify zero roots of a tree, associated with the discharge of bits.

2. The method according to claim 1, characterized in that each of the bits of the bits associated with only one of the bits of each coefficient of elementary waves.

3. The method according to claim 1, characterized in that the stage of encoding bits includes determining which bits indicate the zero roots of the tree, and the classification of each zero as a stand-alone zero or zero root of the tree.

4. The method according to claim 3, characterized in that some of the coefficients of the elementary waves are descendants of some other factors of the elementary waves, and in which stage definition contains a passage of the tree of the descendants of bits associated with one of these some factors of elementary waves, the bits associated with these other factors of elementary waves, to detect zero roots of the tree.

5. The method according to claim 1, characterized in that the stage of creating includes creating a different code levels, where each level is associated with different image resolution.

6. The method according to claim 5, characterized in that the levels that are associated with a lower resolution associated with higher discharges.

7. The method according to claim 1, characterized in that the stage of creation of the coefficients of elementary waves comprises establishing coefficients of intensity levels, which indicate the intensity of image elements, the transformation coefficients of the intensity levels in the sub-bands of elementary waves.

8. Device coding using zero trees coefficients of elementary waves containing the information carrier, configured to read the system based on the processor, the storage medium stores instructions that provide execution by the processor generate coefficients of elementary waves, which indicate the image, while the bits of each coefficient of elementary waves associated with various bits bits so that each discharge of bits associated with one of the bits of each coefficient of elementary waves and in relation to each of the bits of the bit encoding of the associated bits to specify zero roots of the tree that are associated with the discharge of bits.

9. The device according to claim 8, characterized in that each of the bits of the bits associated with only one of the bits of each coefficient of elementary waves.

10. The device according to claim 8, wherein the storage medium contains instructions that provide execution by the processor determine which bits indicate the zero roots of the tree, and the classification of each zero as a stand-alone zero or zero root of the tree.

11. The device according to claim 10, characterized in that some of the coefficients of the elementary waves are descendants of some other factors of the elementary waves, while the media and the formation contains instructions, ensure the implementation of the processor passage of the tree of the descendants of bits associated with one of these some factors of elementary waves, the bits associated with these other factors of elementary waves, to detect zero roots of the tree.

12. The device according to claim 8, wherein the storage medium contains instructions that facilitate the execution processor create different code levels, where each level is associated with different image resolution.

13. The device according to item 12, characterized in that the levels that are associated with lesser permissions associated with higher discharges.

14. Computer system coding using zero trees coefficients of elementary waves, containing a processor, and memory storing a program for execution by a processor generate coefficients of elementary waves, which indicate the image, while the bits of each coefficient of elementary waves associated with various bits of bits, so that each discharge of bits associated with one of the bits of each coefficient of elementary waves and in relation to each of the bits of the bit encoding of the associated bits to specify zero roots of the tree that are associated with the discharge of bits.

15. Computer system 14, characterized in that the AC is ery of bits bits associated with only one of the bits of each coefficient of elementary waves.

16. Computer system 14, characterized in that the program provides for execution by the processor coding bits by determining which of the bits indicates zeros, and classify each zero as a stand-alone zero or zero root of the tree.

17. A computer system according to item 16, characterized in that some of the coefficients of the elementary waves are descendants of some other factors of the elementary waves and in which the processor determines which of the bits are zeros, through passage of the tree of the descendants of bits associated with one of these some factors of elementary waves, the bits associated with these other factors of the elementary waves for the detection of the zero root of the tree.

18. Computer system 14, characterized in that the program provides for execution by the processor generate coefficients of elementary waves through the creation of various levels of code, where each level is associated with different image resolution.

**Same patents:**

**FIELD: coding elementary-wave data by means of null tree.**

**SUBSTANCE: proposed method includes generation of elementary-wave ratios pointing to image. In the process bits of each elementary-wave ratio are associated with different bit places so that each place is associated with one of bits of each elementary-wave ratio and associated bits are coded with respect to each place of bits to point to null tree roots. Each place of bits is also associated only with one of bits of each elementary-wave ratio. Computer system 100 for coding elementary-wave ratios by means of null tree has processor 112 and memory 118 saving program that enables processor 112 to generate elementary-wave ratios pointing to image. Processor 112 functions to code bits of each place to point to null tree roots associated with place of bits.**

**EFFECT: enhanced data compression speed.**

**18 cl, 7 dwg**

FIELD: text optical recognition.

SUBSTANCE: method includes following stages: separating data of bitmap image on levels with varying complication degree; separating these data on objects; determining membership of each objects at one of complication levels; setting hierarchical connections between objects of different complication levels; setting interconnection between objects of same complication level; analyzing properties of objects, including at least following steps: making a theory about properties of analyzed object, checking theory concerning properties of analyzed objects, correcting data concerning properties of connected objects of same or different complication levels.

EFFECT: higher quality, simplified processing, higher error sensitivity.

6 cl, 3 dwg

FIELD: communications.

SUBSTANCE: previously, at transmitting and receiving sides random quadratic matrix is identically generated with size m×m elements and two pairs of random key matrices with sizes N×m and m×N elements. From k frames of colored images with sound signal k of matrices of quantized counts of colored moving image are formed with size M×M×k elements and Z-digit sound vector. Received matrices are transformed to digital form on basis of presentation of each of them in form of result of multiplication of three matrices: random rectangular matrix with size N×m elements, random quadratic matrix with size m×m elements and random rectangular matrix with size m×N elements. Into digital communication channel elements of rectangular matrices of size N×m and m×N elements are transferred. Restoration of images is performed in reversed order.

EFFECT: higher speed of data transfer.

5 cl, 23 dwg

FIELD: optical object identification means.

SUBSTANCE: identification element of optical seal is lit by passing optical probing emission, its optical image is projected into place of multi-element photo-detector, voltages U_{n} are recorded at outputs of elements of photo-detector and aforementioned signals are used to form an optical image of seal, which is recorded and then used to compare to control optical image of seal. During recording process aforementioned voltages are measured and also measured are exposition time spans appropriate for them in case of presence pot absence of identification element in optical track, and also voltages during replacement of identification element by black body and measured values are used for calculation by given method of a block of mathematical expressions, representing an optical image of seal.

EFFECT: optical image, free from influence of alternation of a parameters of optical track and photo-detector elements.

1 dwg