An image transmission method, device and equipment of joint coding and storage medium

Abstract

The application provides a joint coding image transmission method, device and equipment and a storage medium. By increasing the sending of original bit information and reducing the sending of check bit information, lossless transmission of images is realized by using double LDPC joint coding without increasing redundancy. Meanwhile, low-frequency information is considered as the increased original bit information, unequal power modulation is used by taking the non-equivalent characteristics of the low-frequency information into account, and unequal protection is realized by using corresponding redundancy information at the decoding end, so that performance gain is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication coding, and particularly relates to a joint coding image transmission method and device, equipment and a storage medium. BACKGROUND

[0002] Image transmission technology is an important research direction in the field of modern communication. The traditional image transmission scheme adopts a separate source channel coding mode, that is, source coding and channel coding are independent of each other. However, in the case of limited code length, source compression and channel interference can cause serious error propagation, resulting in a decline in transmission quality, so the traditional scheme is not suitable for low-complexity image transmission scenarios.

[0003] The proposal of a joint source channel coding (JSCC) scheme provides a new idea for solving the above problems. The joint coding scheme based on double LDPC codes uses one LDPC code to implement source coding and another LDPC code to implement channel coding at the sending end, and iteratively decodes by using source redundancy information and received symbol information at the receiving end, which can realize low-complexity and low-power information transmission in the case of limited code length.

[0004] In the prior art, the basic process of the joint coding image transmission scheme based on double LDPC codes is as follows: first, the original image is subjected to 8x8 pixel block blocking operation, and discrete cosine transform (DCT) and quantization processing are performed on each pixel block, and the quantization result is encoded with 8-bit binary to obtain a binary bit sequence; then, according to the sparsity requirement of the transmission frame, when the sparsity of the transmission frame is greater than a preset threshold, the transmission frame is evenly decomposed into multiple transmission frames, and a certain number of "0" bits are supplemented to the decomposed frames to meet the sparsity requirement of lossless source coding; finally, the processed sequence is sequentially subjected to source coding and channel coding, and after modulation, it is sent to the channel for transmission.

[0005] However, the above prior art has the following disadvantages: in order to meet the requirement of lossless source coding, although the frame decomposition and "0" supplement operation can avoid too high error floor caused by too large source entropy, this method introduces more redundancy information, reducing the transmission efficiency; at the same time, frame reconstruction is required at the receiving end, increasing the complexity of the system. In addition, the existing scheme fails to fully utilize the different importance characteristics of low-frequency information and high-frequency information in image signals, and uses the same protection strategy for all information, failing to optimize the transmission performance.

[0006] In view of this, the present application is proposed. SUMMARY

[0007] The application discloses a joint coding image transmission method, device, equipment and storage medium, and aims to realize joint coding image transmission meeting lossless source coding without increasing redundancy.

[0008] The first embodiment of the application provides a joint coding image transmission method, which comprises the following steps:

[0009] The original image block is subjected to a blocking operation, and each pixel block is subjected to discrete cosine transformation and quantization processing; the quantization result is subjected to binary coding in a sparsest coding mode to obtain a binary bit sequence corresponding to each pixel block;

[0010] The binary bit sequences corresponding to the plurality of pixel blocks are combined into a sequence to be coded and transmitted in a non-uniform arrangement mode; the sparsity of the sequence to be coded and transmitted is calculated, and the sequence to be coded and transmitted is divided into a low-frequency information bit sequence and a high-frequency information bit sequence according to the sparsity;

[0011] A source coding check matrix and a channel coding check matrix are selected according to the sparsity and code length requirement; the sequence to be coded and transmitted is subjected to source coding to obtain a compressed bit sequence and subjected to channel coding to obtain a check bit sequence;

[0012] According to the sparsity of the sequence to be coded and transmitted, the low-frequency information bit sequence is selected as the original information bit to be punctured, and a corresponding number of the compressed bit sequence and the check bit sequence are punctured to form a transmission sequence;

[0013] The low-frequency information bit sequence is subjected to unequal power modulation, and the compressed bit sequence and the check bit sequence remaining after puncturing are subjected to equal power modulation to form a modulation signal and then transmitted.

[0014] Preferably, the method further comprises the following steps: at the receiving end, according to whether the bit sequence corresponding to each variable node participates in transmission and the corresponding modulation mode, initialization calculation of decoding information is performed; the joint coding check matrix and the belief propagation algorithm are used to decode the received signal to obtain a decoded bit sequence;

[0015] The decoded bit sequence is subjected to binary inverse coding, inverse quantization and inverse discrete cosine transformation to obtain a recovered image.

[0016] Preferably, the sparsest coding mode comprises the following steps: the occurrence proportion of each integer value after quantization in all quantized values is counted;

[0017] In the order from large to small according to the occurrence proportion, the binary bit sequences with sparsities from small to large are sequentially used for representation.

[0018] Preferably, the multiple pixel blocks are combined into the sequence to be encoded and transmitted by using a non-uniform arrangement mode, specifically:

[0019] For each pixel block matrix after the discrete cosine transform, the Z-shaped mode is used for traversal sorting to obtain a pixel sequence in which the low-frequency information pixels are in front and the high-frequency information pixels are in back.

[0020] The multiple pixel blocks are arranged into a matrix in the Z-shaped mode and converted into a vector in a column traversal mode from top to bottom, and each element in the vector is binary encoded by using the sparsest encoding mode to obtain the sequence to be encoded and transmitted.

[0021] Preferably, the unequal power modulation mode is:

[0022] Bit 1 with a low occurrence probability in the low-frequency information bit sequence is assigned a first energy value, and bit 0 with a high occurrence probability is assigned a second energy value, wherein the first energy value is greater than the second energy value.

[0023] Bit 1 and bit 0 in the compressed bit sequence and the check bit sequence remaining after the puncturing are modulated into equal energy values.

[0024] Preferably, the initialization calculation of the decoding information includes:

[0025] For the low-frequency information bit sequence participating in sending, the initial decoding information is: wherein y l is a signal value of the low-frequency information bit sequence received at the receiving end, is the sparsity of the low-frequency information bit sequence, is the noise variance;

[0026] For the high-frequency information bit sequence not participating in sending, the initial decoding information is , is the sparsity of the low-frequency information bit sequence;

[0027] For the compressed bit sequence and the check bit sequence participating in sending, the initial decoding information is , y i is a value of the i th symbol received, which contains the superposition of the sending signal and the channel noise;

[0028] For the compressed bit sequence and the check bit sequence not participating in sending, the initial decoding information is set to zero.

[0029] Preferably, the sending length of the low-frequency information bit sequence is adaptively adjusted according to the channel signal-to-noise ratio and the sparsity of the sequence to be encoded and transmitted.

[0030] The second embodiment of the present application provides a joint coding image transmission device, comprising:

[0031] An image preprocessing module is configured to perform a block operation on an original image block, perform a discrete cosine transform and quantization processing on each pixel block, perform binary coding on the quantization result by using a sparsest coding mode, and obtain a binary bit sequence corresponding to each pixel block.

[0032] A sequence combination module is configured to combine the binary bit sequences corresponding to the pixel blocks into a sequence to be coded and transmitted by using a non-uniform arrangement mode, calculate the sparsity of the sequence to be coded and transmitted, and divide the sequence to be coded and transmitted into a low-frequency information bit sequence and a high-frequency information bit sequence according to the sparsity.

[0033] An encoding module is configured to select a source coding check matrix and a channel coding check matrix according to the sparsity and a code length requirement, perform source coding on the sequence to be coded and transmitted to obtain a compressed bit sequence, and perform channel coding to obtain a check bit sequence.

[0034] A sending adjustment module is configured to select the low-frequency information bit sequence as original information bits to be sent more, and puncture a corresponding number of the compressed bit sequence and the check bit sequence to form a sending sequence according to the sparsity of the sequence to be coded and transmitted.

[0035] An unequal power modulation module is configured to perform unequal power modulation on the low-frequency information bit sequence, and perform equal power modulation on the compressed bit sequence and the check bit sequence remaining after puncturing, and send a modulation signal formed after modulation.

[0036] The third embodiment of the present application provides a joint coding image transmission device, comprising a memory and a processor, the memory stores a computer program, and the computer program can be executed by the processor to implement the joint coding image transmission method according to any one of the above.

[0037] The fourth embodiment of the present application provides a computer readable storage medium, characterized in that it stores a computer program, and the computer program can be executed by a processor of a device where the computer readable storage medium is located to implement the joint coding image transmission method according to any one of the above.

[0038] Based on the joint coding image transmission method, device and equipment and storage medium provided by the application, by increasing the sending of original bit information and reducing the sending of check bit information, the lossless transmission of images is realized by using double LDPC joint coding without increasing redundancy, and the performance gain is realized by considering the low-frequency information as the increased original bit information, using unequal power modulation by using the non-equivalent characteristics of the low-frequency information, and realizing unequal protection by using the corresponding redundancy information at the decoding end. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is a flowchart of a joint coding image transmission method provided by the first embodiment of the application;

[0040] Figure 2 is a joint coding image transmission diagram based on double LDPC code provided by the application.

[0041] Figure 3 is a module diagram of a joint coding image transmission device provided by the second embodiment of the application. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0043] In order to better understand the technical solutions of the application, the embodiments of the application will be described in detail below with reference to the drawings.

[0044] The application discloses a joint coding image transmission method, device, equipment and storage medium, and aims to realize joint coding image transmission meeting lossless source coding without increasing redundancy.

[0045] Please refer to Figure 1 and Figure 2 The joint coding image transmission method provided by the first embodiment of the application can be executed by a joint coding image transmission device based on an unequal protection mechanism (hereinafter referred to as a transmission device), in particular, by one or more processors in the transmission device, to at least realize the following steps:

[0046] S101, performing a block operation on an original image block, performing discrete cosine transform and quantization processing on each pixel block, using a sparsest coding mode to perform binary coding on the quantization result, and obtaining a binary bit sequence corresponding to each pixel block;

[0047] In this embodiment, the transmission device can be a desktop computer, laptop computer, server, workstation, or other terminal with data processing capabilities, which can establish a communication connection with the receiving end. The transmission device and the receiving end can be equipped with corresponding operating systems and application software, and the functions required in this embodiment are realized through the combination of the operating system and application software.

[0048] In this embodiment, for a pixel size of The image is divided into blocks of 2k×2k pixels, denoted as . For each pixel block, a Discrete Cosine Transform (DCT) is performed, followed by quantization using a 2k×2k quantization matrix to obtain the quantized result. Here, the quantization result is encoded using 8 bits, employing the sparsest encoding method.

[0049] The sparsest encoding method includes: statistically analyzing the proportion of each integer value after quantization among all quantized values; and representing each integer value with a binary bit sequence of increasing sparsity in descending order of the proportion of occurrence.

[0050] Let's illustrate with an example:

[0051] First, given a 512×512 image, let k=3, i.e., 8×8 pixels per block, and perform block division, denoted as k = 3. The DCT transformation is performed on each pixel block, and then an 8×8 quantization matrix is ​​used to obtain the quantization result. The steps are as follows: After quantization, the proportion of the integer [-127, 128] among all quantized values ​​is calculated, and denoted as [formula missing]. ,right Perform descending sorting;

[0052] Then, based on the proportion from large to small, the data is represented by binary bits with sparsity from small to large (the sparsity of the sequence 00000000 is 0, and the sparsity of 00000001 or 00000010, which contain only one bit "1", is 1 / 8).

[0053] Statistics of all Q i The proportion of integers is determined, and then the first 7 numbers are sorted from largest to smallest, which are 0, 1, -1, -2, -3, 3, etc. Therefore, they are represented as 00000000, 00000001, 00000010, 00000100, 00001000, 00010000, 0010000, 00100000. In addition, the value -126 is the last one, so it is represented as 11111111.

[0054] S102, using a non-uniform arrangement method, the binary bit sequences corresponding to multiple pixel blocks are combined into a sequence to be encoded and transmitted, the sparsity of the sequence to be encoded and transmitted is calculated, and the sequence to be encoded and transmitted is divided into a low-frequency information bit sequence and a high-frequency information bit sequence according to the sparsity.

[0055] In this embodiment, based on the limitations of actual transmission bandwidth and code length requirements, t pixel blocks are selected from left to right to form a non-uniformly arranged sequence s to be encoded and transmitted. An image can generate multiple sequences to be encoded and transmitted. The sparsity of each sequence s is calculated as follows: With the greatest As .

[0056] It should be noted that this applies to each pixel block after DCT transformation. Matrix, using The x-th row and y-th column of the matrix are arranged and sorted in a “Z” pattern (1,1), (1,2), (2,1), (3,1), (2,2), (1,3) to obtain a sequence of low-frequency information pixels first and high-frequency information pixels last.

[0057] Arrange the selected t pixel blocks into a shape with dimension t×2 according to the steps described above. 2k The matrix is ​​transformed into a 1×2 dimension matrix by traversing columns from top to bottom. 2k The vector t is then quantized, and each element of the vector is encoded using 8-bit binary representation to obtain the sequence s to be encoded and transmitted. l s h ], where the sparsity of s is ,according to The size of s divides s into two parts, i.e., s = [s l s h ], s l This represents the binary bit sequence corresponding to low-frequency information, with a sparsity of . s h The binary bit sequence representing high-frequency information has a sparsity of . .

[0058] To illustrate with an example: If we select t = 8 pixels as a transmission frame, then an image is divided into 512 frames. The source code length is 4096. The sparsity of each sequence s to be transmitted can then be calculated. ,in Taking the first transmission frame as an example, take the quantized matrices Q1 to Q8, place the pixel at (1,1) of Q1 at the beginning, followed by pixels at (1,2) and (2,1), then pixels at (2,2) and (1,3), and so on, increasing sequentially, and then convert it into a 1×64 vector; then perform the same operation on matrices Q2 to Q8, arranging them into an 8×64 matrix, and traversing this 8×64 matrix from top to bottom, converting it into a 1×512 vector. Using the sparsest coding method for binary representation, the sequence to be encoded and transmitted, s=[s... l s h ],calculate Therefore, the first 640 bits are used as s l The remaining 3466 bit sequence is used as s h , forming s=[s l s h ],in .

[0059] S103, Select the source coding parity matrix and the channel coding parity matrix according to the sparsity and code length requirements, perform source coding on the sequence to be encoded and transmitted to obtain a compressed bit sequence, and perform channel coding to obtain a parity bit sequence;

[0060] according to In addition to the code length requirements, a suitable source code parity check matrix should be selected. and a channel coding check matrix Combining these elements yields an encoding matrix of a certain code length. For a given sequence s to be encoded and transmitted, source coding and channel coding are performed, i.e. ;

[0061] To illustrate with an example, we choose a regular LDPC code with a node degree of 3 and a source code length of 4096. Therefore, a regular LDPC code of size 4096*1024 is selected as the source coding verification matrix. 1024*2048 is used as the channel coding check matrix. Then, they are combined into a single identity matrix of size 1024*1024 to obtain a joint encoding matrix. ;

[0062] For a given channel check matrix Perform Gaussian elimination to obtain the corresponding G. c Then, source coding and channel coding are performed on the first frame sequence, i.e. The length of c is 1024, and the length of p is also 1024. Because s lis 640, so here we only need to puncture the same number of 640 bit sequences of p, so the sending sequence becomes [s l c’p’], where c’=c, p’ is a part of p.

[0063] S104, according to the sparsity of the sequence to be encoded, select the low-frequency information bit sequence as the original information bit to be sent, puncture a corresponding number of compressed bit sequences and check bit sequences to form a sending sequence;

[0064] According to the sparsity of sequence s, select a certain number of original information bits s', puncture a corresponding number of c and p, and the remaining part is recorded as [c' p'], to form a new sending sequence [s' c' p']; According to the sparsity of sequence s, select a certain number of original information bits s', puncture a corresponding number of c and p, and the remaining part is recorded as [c' p'], to form a new sending sequence [s' c' p'];

[0065] According to the sparsity of sequence s, select a certain number of original information bits s', puncture a corresponding number of c and p, and the remaining part is recorded as [c' p'], to form a new sending sequence [s' c' p']; l , that is, s' = s l , it should be noted that when is very small, this also includes the case of sl=0;

[0066] Puncture a corresponding number of c and p, and preferentially puncture check bits p. If the corresponding number is not enough, puncture compressed bits c, that is, form a new sending sequence [s l c' p'];

[0067] S105, unequal power modulation is performed on the low-frequency information bit sequence, and equal power modulation is performed on the compressed bit sequence and the check bit sequence remaining after puncturing, and the modulated signal is sent.

[0068] In this embodiment, after unequal power modulation is performed on the sending sequence s' and equal power modulation is performed on [c' p'], the unequal power modulation means that the bit "1" with a smaller probability is given more energy, and the bit "0" with a larger probability is given less energy, that is, the bit "1" in s l is modulated as , and the bit "0" in s l is modulated as , and the bit "1" and the bit "0" in [c' p'] are modulated as and , respectively, where represents unit energy.

[0069] It should be noted that the unit energy is usually assumed to be 1, that is, =1, and according to , the bit "1" in s l is modulated as​ , s l bit '0' in [c' p'] is modulated as and bit '1' in [c' p'] is modulated as and and then transmitted.

[0070] In a possible implementation of the present application, the method further comprises: at the receiving end, performing initialization calculation of decoding information according to whether the bit sequence corresponding to each variable node is transmitted and the corresponding modulation mode, and performing decoding on the received signal by using the joint encoding check matrix and the belief propagation algorithm to obtain a decoded bit sequence;

[0071] Performing binary inverse coding, inverse quantization and inverse discrete cosine transform operations on the decoded bit sequence to obtain a recovered image.

[0072] In the embodiment, at the receiving end, initialization calculation of decoding information is performed according to whether the bit sequence corresponding to each variable node is transmitted and the corresponding modulation mode, log-likelihood information L is obtained, and decoding is performed by using the joint encoding check matrix and the belief propagation algorithm; for different transmission frames, the bit sequence obtained by decoding is subjected to 8-bit binary inverse coding, corresponding inverse quantization and inverse DCT operations to obtain a recovered image.

[0073] The key of the initialization calculation of decoding information lies in how to fully utilize the redundancy of information.

[0074] For the low-frequency information bit sequence participating in transmission, the initial decoding information is wherein, y l is a signal value of the low-frequency information bit sequence received at the receiving end, is the sparsity of the low-frequency information bit sequence, is a noise variance;

[0075] For the high-frequency information bit sequence not participating in transmission, the initial decoding information is , is the sparsity of the low-frequency information bit sequence;

[0076] For the compressed bit sequence and the check bit sequence participating in transmission, the initial decoding information is , y i is a value of the i th symbol received, which contains the superposition of the transmitted signal and channel noise;

[0077] For the compressed bit sequence and the check bit sequence not participating in transmission, the initial decoding information is set to zero.

[0078] It should be noted that if the signal-to-noise ratio is poor, the length of s l needs to be reduced, if the signal-to-noise ratio is good, the length of s l needs to be increased; if the sparsity of s is low, the length of s l needs to be reduced, and may even be 0, if the sparsity of s is high, the length of s l needs to be increased. The image transmission under different channel conditions is obtained.

[0079] It should be particularly noted that if different LDPC code types are selected, the selection of s l and s h needs to be adjusted according to different signal-to-noise ratios and different sparsities of image transmission frames to achieve the best effect.

[0080] Please refer to Figure 3 , the second embodiment of the present application provides a joint coding image transmission device, comprising:

[0081] An image preprocessing module 201 is configured to perform a blocking operation on an original image block, perform discrete cosine transform and quantization processing on each pixel block, and perform binary coding on the quantization result in a sparsest coding manner to obtain a binary bit sequence corresponding to each pixel block.

[0082] A sequence combination module 202 is configured to combine the binary bit sequences corresponding to the pixel blocks into a sequence to be coded and transmitted in a non-uniform arrangement manner, calculate the sparsity of the sequence to be coded and transmitted, and divide the sequence to be coded and transmitted into a low-frequency information bit sequence and a high-frequency information bit sequence according to the sparsity.

[0083] An encoding module 203 is configured to select a source coding check matrix and a channel coding check matrix according to the sparsity and the code length requirement, perform source coding on the sequence to be coded and transmitted to obtain a compressed bit sequence, and perform channel coding to obtain a check bit sequence.

[0084] A sending adjustment module 204 is configured to select the low-frequency information bit sequence as the original information bit to be sent, and puncture a corresponding number of the compressed bit sequence and the check bit sequence to form a sending sequence according to the sparsity of the sequence to be coded and transmitted.

[0085] An unequal power modulation module 205 is configured to perform unequal power modulation on the low-frequency information bit sequence, and perform equal power modulation on the compressed bit sequence and the check bit sequence remaining after puncturing to form a modulation signal and then send the modulation signal.

[0086] The third embodiment of the present application provides a joint coding image transmission device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement the joint coding image transmission method according to any one of the above.

[0087] The fourth embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program can be executed by a processor of a device where the computer readable storage medium is located to implement the joint coding image transmission method according to any one of the above.

[0088] Based on the joint coding image transmission method, device, equipment and storage medium provided by the present application, by increasing the sending of original bit information and reducing the sending of check bit information, the lossless transmission of images is realized by using double LDPC joint coding without increasing redundancy, and considering that low-frequency information is used as the increased original bit information, unequal power modulation is used by using the non-equivalent characteristics of the low-frequency information, and unequal protection is realized by using the corresponding redundancy information at the decoding end, so that performance gain is realized.

[0089] Exemplarily, the computer program in the third embodiment and the fourth embodiment of the present application can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the joint coding image transmission device. For example, the device in the second embodiment of the present application.

[0090] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the joint coding image transmission method, and is connected with all parts of the joint coding image transmission method through various interfaces and lines.

[0091] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the joint coding image transmission method by running or executing the computer program and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function (such as a sound playing function, a text conversion function, etc.), and the like; and the data storage area can store data created according to the use of the mobile phone (such as audio data, text message data, etc.), and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0092] The modules implemented can be stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can realize the steps of the above-mentioned various method embodiments when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the contents included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0093] It should be noted that the apparatus embodiments described above are merely illustrative, and the units described as separate units can or can not be physically separate, and the units shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. In addition, the connection relationship between the modules in the apparatus embodiment provided by the present application indicates that there is a communication connection between them, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0094] The above description is only a preferred embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or replacements within the technical range disclosed by the present application can be easily thought of by those skilled in the art, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A jointly coded image transmission method, characterized in that, include: The original image block is divided into blocks, and each pixel block is subjected to discrete cosine transform and quantization. The quantization result is then encoded into binary using the sparsest coding method to obtain the binary bit sequence corresponding to each pixel block. The sparsest coding method includes: statistically analyzing the proportion of each integer value after quantization among all quantized values; and representing each integer value with a binary bit sequence of increasing sparsity in descending order of the proportion of occurrence. A non-uniform arrangement method is used to combine the binary bit sequences corresponding to multiple pixel blocks into a sequence to be encoded and transmitted. Specifically, for each pixel block matrix after discrete cosine transform, it is traversed and sorted in a zigzag manner to obtain a pixel sequence with low-frequency information pixels first and high-frequency information pixels last; multiple pixel blocks are arranged into a matrix in a zigzag manner and converted into a vector by column traversal from top to bottom; each element in the vector is binary encoded using the sparsest encoding method to obtain the sequence to be encoded and transmitted; the sparsity of the sequence to be encoded and transmitted is calculated, and the sequence to be encoded and transmitted is divided into a low-frequency information bit sequence and a high-frequency information bit sequence according to the sparsity; Based on the sparsity and code length requirements, a source coding parity-check matrix and a channel coding parity-check matrix are selected. The sequence to be encoded and transmitted is then source-coded to obtain a compressed bit sequence, and channel-coded to obtain a parity bit sequence. Based on the sparsity of the sequence to be encoded and transmitted, the low-frequency information bit sequence is selected as the original information bits for additional transmission, and a corresponding number of the compressed bit sequence and the check bit sequence are deleted to form the transmission sequence. The low-frequency information bit sequence is modulated with unequal power, and the remaining compressed bit sequence and check bit sequence after deletion are modulated with equal power to form a modulated signal for transmission. At the receiving end, based on whether the bit sequence corresponding to each variable node participates in transmission and the corresponding modulation method, initialization calculations for decoding information are performed. The received signal is decoded using a joint coding parity-check matrix and a confidence propagation algorithm to obtain a decoded bit sequence. The decoded bit sequence is then subjected to binary inverse encoding, inverse quantization, and inverse discrete cosine transform operations to obtain the recovered image. The initialization calculations for decoding information include: The initial decoding information for the low-frequency information bit sequence that is transmitted is as follows: , where y l It is the signal value received at the receiving end of the low-frequency information bit sequence. It refers to the sparsity of the low-frequency information bit sequence. It is the noise variance; For the high-frequency information bit sequence that was not transmitted, its decoding information is initialized as follows: , It is the sparsity of the high-frequency information bit sequence; The decoding information for the compressed bit sequence and the check bit sequence that are transmitted is initialized as follows: y i It is the value of the received i-th symbol, which includes the superposition of the transmitted signal and channel noise; For the compressed bit sequence and the check bit sequence that were not transmitted, their initial decoding information is set to zero.

2. The image transmission method with joint coding according to claim 1, characterized in that, The unequal power modulation method is as follows: A first energy value is assigned to bit 1, which has a low probability of occurrence in the low-frequency information bit sequence, and a second energy value is assigned to bit 0, which has a high probability of occurrence, wherein the first energy value is greater than the second energy value. Bits 1 and 0 in the remaining compressed bit sequence and the parity bit sequence after deletion are modulated to equal energy values.

3. The image transmission method with joint coding according to claim 1, characterized in that, The transmission length of the low-frequency information bit sequence is adaptively adjusted based on the channel signal-to-noise ratio and the sparsity of the sequence to be encoded and transmitted.

4. A jointly encoded image transmission device, characterized in that, include: The image preprocessing module is used to divide the original image into blocks, perform discrete cosine transform and quantization on each pixel block, and encode the quantization result into binary using the sparsest coding method to obtain the binary bit sequence corresponding to each pixel block. The sparsest coding method includes: statistically analyzing the proportion of each integer value after quantization among all quantized values; and representing each integer value with a binary bit sequence of increasing sparsity in descending order of the proportion of occurrence. The sequence combination module is used to combine the binary bit sequences corresponding to multiple pixel blocks into a sequence to be encoded and transmitted using a non-uniform arrangement method. Specifically, it performs the following steps: for each pixel block matrix after discrete cosine transform, it traverses and sorts the pixels in a zigzag pattern to obtain a pixel sequence with low-frequency information pixels first and high-frequency information pixels last; it arranges multiple pixel blocks into a matrix in a zigzag pattern, converts it into a vector by traversing columns from top to bottom, and performs binary encoding on each element in the vector using the sparsest encoding method to obtain the sequence to be encoded and transmitted; it calculates the sparsity of the sequence to be encoded and transmitted, and divides the sequence to be encoded and transmitted into a low-frequency information bit sequence and a high-frequency information bit sequence based on the sparsity. The encoding module is used to select the source coding parity matrix and the channel coding parity matrix according to the sparsity and code length requirements, perform source coding on the sequence to be encoded and transmitted to obtain a compressed bit sequence, and perform channel coding to obtain a parity bit sequence. The transmission adjustment module is used to select the low-frequency information bit sequence as the original information bits for additional transmission based on the sparsity of the sequence to be encoded and transmitted, and to delete a corresponding number of the compressed bit sequence and the parity bit sequence to form a transmission sequence. The unequal power modulation module is used to perform unequal power modulation on the low-frequency information bit sequence, and to perform equal power modulation on the remaining compressed bit sequence and check bit sequence after deletion, so as to form a modulated signal for transmission. At the receiving end, based on whether the bit sequence corresponding to each variable node participates in transmission and the corresponding modulation method, initialization calculations for decoding information are performed. The received signal is decoded using a joint coding parity-check matrix and a confidence propagation algorithm to obtain a decoded bit sequence. The decoded bit sequence is then subjected to binary inverse encoding, inverse quantization, and inverse discrete cosine transform operations to obtain the recovered image. The initialization calculations for decoding information include: The initial decoding information for the low-frequency information bit sequence that is transmitted is as follows: , where y l It is the signal value received at the receiving end of the low-frequency information bit sequence. It refers to the sparsity of the low-frequency information bit sequence. It is the noise variance; For the high-frequency information bit sequence that was not transmitted, its decoding information is initialized as follows: , It is the sparsity of the high-frequency information bit sequence; The decoding information for the compressed bit sequence and the check bit sequence that are transmitted is initialized as follows: y i It is the value of the received i-th symbol, which includes the superposition of the transmitted signal and channel noise; For the compressed bit sequence and the check bit sequence that were not transmitted, their initial decoding information is set to zero.

5. A jointly encoded image transmission device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be executed by the processor to implement a jointly encoded image transmission method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The device contains a computer program that can be executed by a processor of the device in which the computer-readable storage medium is located, to implement a jointly encoded image transmission method as described in any one of claims 1 to 3.

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