Image compression system, device and method

Abstract

The present invention relates to the field of image processing, and in particular to an image compression system, device and method, which are used to solve the problem that existing image compression methods are often difficult to achieve a good balance between compression efficiency and image quality, especially when processing high-resolution images, the compressed image may have obvious quality loss; the system uses intelligent segmentation technology and then compresses separately, thereby achieving efficient image compression while ensuring the quality of the compressed image and improving the perceived quality of the image; quality monitoring is also performed after compression, which can accurately reflect the quality of the compressed image and provide a reliable basis for adjusting compression parameters. The system achieves efficient image compression while ensuring image quality, achieves a good balance between compression efficiency and image quality, is suitable for different types of images and compression requirements, and has strong versatility and expansibility.

Description

Technical Field

[0001] The present invention relates to the field of image processing, and in particular to an image compression system, device and method. Background Art

[0002] With the widespread application of digital images and the rapid development of Internet technology, the amount of image data has exploded. A large amount of image data needs to be effectively stored and quickly transmitted, so image compression technology has become particularly important. However, image data usually has a large amount of data, and direct transmission and processing will consume a lot of storage space and computing resources. Therefore, image compression technology has become the key to solving this problem.

[0003] Although existing image compression methods can reduce the size of image data to a certain extent, they are often accompanied by a loss of image quality. Especially when processing high-resolution images, the compressed image may suffer from significant quality loss. Therefore, how to achieve a good balance between compression efficiency and image quality is an urgent problem to be solved in the field of image processing. Summary of the invention

[0004] In order to overcome the above-mentioned technical problems, the purpose of the present invention is to provide an image compression system, device and method, which solves the problem that existing image compression methods are often difficult to achieve a good balance between compression efficiency and image quality, especially when processing high-resolution images, the compressed image may have obvious quality loss.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An image compression system, comprising:

[0007] The data acquisition module is used to obtain the reference image i according to the historical data, obtain the data analysis information of the reference image i, and send the data analysis information to the data analysis module; wherein the data analysis information includes the compression value YS and the time difference value SS;

[0008] A data analysis module, used for obtaining a data analysis coefficient SF according to the data analysis information, and sending the data analysis coefficient SF to the image segmentation module;

[0009] The specific process of the data analysis module obtaining the data analysis coefficient SF is as follows:

[0010] The compression value YS and the time difference value SS are quantized, the values ​​of the compression value YS and the time difference value SS are extracted, and the values ​​are substituted into the formula for calculation. The data analysis coefficient SF is obtained, where e is a mathematical constant, ε is a preset error adjustment factor, ε=0.938, α1 and α2 are preset weight factors corresponding to the set compression value YS and time difference value SS, α1 and α2 satisfy α1>α2>1.32, α1=2.13, α2=1.69;

[0011] Send the data analysis coefficient SF to the image segmentation module;

[0012] An image segmentation module, used to obtain a selected reference image according to the data analysis coefficient SF, obtain a segmentation reference value according to the selected reference image, and segment the image to be compressed according to the segmentation reference value to obtain image blocks Tj, and send the image blocks Tj to the image compression module;

[0013] An image compression module is used to compress all image blocks Tj simultaneously, obtain compressed image blocks Yj after compression, and send the compressed image blocks Yj to the compressed image storage module;

[0014] The compressed image storage module is used to store the compressed image block Yj, generate a quality monitoring instruction, and send the quality monitoring instruction to the quality monitoring module.

[0015] As a further solution of the present invention: the specific process of the data acquisition module obtaining the compression value YS is as follows:

[0016] Get the disk size of the image to be compressed and mark it as the pre-compression value YZ;

[0017] Obtain all images with the same pre-compression occupation value YZ from the historical data, and mark them as reference images i, where i=1, 2, 3, ..., n, where n is a positive integer, n represents the total number of reference images, and i represents the number of any reference image;

[0018] The disk size occupied by the compressed image during the compression process of the reference image i is obtained, and it is marked as the post-compression value YH. The difference between the pre-compression value YZ and the post-compression value YH is obtained, and it is marked as the compression value YS.

[0019] As a further solution of the present invention: the specific process of the data acquisition module acquiring the time difference value SS is as follows:

[0020] Get the time length of the reference image i to be compressed, and mark it as the compression length value YC, get the time length of the image blocks divided into the reference image i to be compressed, and mark it as the block length value KC, get the average value of all block length values ​​KC, and mark it as the block mean KJ, get the difference between the maximum block length value KC and the minimum block length value KC, and mark it as the long difference CC, quantize the compression length value YC, the block mean KJ and the long difference CC, extract the values ​​of the compression length value YC, the block mean KJ and the long difference CC, and substitute them into the formula for calculation, according to the formula The time difference value SS is obtained, where s1, s2 and s3 are the preset proportional coefficients corresponding to the set compression length value YC, block mean KJ and length difference CC respectively, and s1, s2 and s3 satisfy s1+s2+s3=1, 0<s3<s2<s1<1, and s1=0.41, s2=0.33, s3=0.26.

[0021] As a further solution of the present invention: the specific process of the image segmentation module obtaining the image block Tj is as follows:

[0022] Compare the data analysis coefficient SF with the preset data analysis threshold SFy:

[0023] If the data analysis coefficient SF ≥ the data analysis threshold SFy, the reference image i is marked as a compression qualified image;

[0024] Randomly extracting a preset number of compressed qualified images from all compressed qualified images, marking them as selected reference images, obtaining the segmentation byte value when the selected reference image is segmented, and obtaining the average value of all segmentation byte values, and marking it as the segmentation reference value;

[0025] The image to be compressed is segmented according to the segmentation reference value, and image blocks Tj are obtained from front to back according to the front and back positions in the image to be compressed, where j=1, 2, 3, ..., m, where m is a positive integer, m represents the total number of image blocks, and j is the number of any image block, and the image block Tj is sent to the image compression module.

[0026] As a further solution of the present invention: the image compression system further includes:

[0027] The quality monitoring module is used to play the compressed image block Yj continuously according to the number after receiving the quality monitoring instruction, obtain the quality monitoring information of the continuous playback process, obtain the quality monitoring coefficient ZL according to the quality monitoring information, and send the quality monitoring coefficient ZL to the abnormal alarm module; wherein the quality monitoring information includes the freeze value KD and the abnormal picture value YH.

[0028] As a further solution of the present invention: the specific process of the quality monitoring module obtaining the quality monitoring coefficient ZL is as follows:

[0029] After receiving the quality monitoring instruction, the compressed image blocks Yj are played continuously according to the numbers, wherein the continuous play means that after the compressed image block Y1 is played, the compressed image block Y2 is played, until all the compressed image blocks Yj are played, and the playback is performed according to the preset playback multiple;

[0030] Obtain the number of freezes and abnormal screens during the continuous playback of the compressed image block Yj, and mark them as freeze value KD and abnormal screen value YH, respectively, where the abnormal screen includes black screen, flower screen, and flashing screen;

[0031] The jamming value KD and the abnormal picture value YH are quantified, the values ​​of the jamming value KD and the abnormal picture value YH are extracted, and substituted into the formula for calculation. The quality monitoring coefficient ZL is obtained, where μ is the preset error adjustment factor, μ=1.112, z1 and z2 are the preset proportional coefficients corresponding to the set jam value KD and the abnormal picture value YH, respectively, z1 and z2 satisfy z1+z2=1, 0<z1<z2<1, and z1=0.43 and z2=0.57;

[0032] The quality monitoring coefficient ZL is sent to the abnormal alarm module.

[0033] As a further solution of the present invention: the image compression system further includes:

[0034] The abnormal alarm module is used to sound a compression abnormality alarm according to the quality monitoring coefficient ZL.

[0035] As a further solution of the present invention: the specific process of the abnormal alarm module sounding the compression abnormal alarm is as follows:

[0036] Compare the quality monitoring coefficient ZL with the preset quality monitoring threshold ZLy:

[0037] If the quality monitoring coefficient ZL ≥ the quality monitoring threshold ZLy, a compression abnormality alarm sounds.

[0038] As a further solution of the present invention: an image compression method comprises the following steps:

[0039] Step 1: The data acquisition module obtains the reference image i according to the historical data, and obtains the data analysis information of the reference image i, wherein the data analysis information includes the compression value YS and the time difference value SS, and sends the data analysis information to the data analysis module;

[0040] Step 2: The data analysis module obtains the data analysis coefficient SF according to the data analysis information, and sends the data analysis coefficient SF to the image segmentation module;

[0041] Step 3: The image segmentation module obtains a selected reference image according to the data analysis coefficient SF, obtains a segmentation reference value according to the selected reference image, and segments the image to be compressed according to the segmentation reference value to obtain image blocks Tj, and sends the image blocks Tj to the image compression module;

[0042] Step 4: The image compression module compresses all the image blocks Tj simultaneously, obtains the compressed image block Yj after the compression is completed, and sends the compressed image block Yj to the compressed image storage module;

[0043] Step 5: The compressed image storage module stores the compressed image block Yj, generates a quality monitoring instruction, and sends the quality monitoring instruction to the quality monitoring module;

[0044] Step 6: After receiving the quality monitoring instruction, the quality monitoring module plays the compressed image block Yj continuously according to the number, obtains the quality monitoring information of the continuous playback process, wherein the quality monitoring information includes the jamming value KD and the abnormal picture value YH, obtains the quality monitoring coefficient ZL according to the quality monitoring information, and sends the quality monitoring coefficient ZL to the abnormal alarm module;

[0045] Step 7: The abnormal alarm module sounds a compression abnormal alarm according to the quality monitoring coefficient ZL.

[0046] As a further solution of the present invention: an image compression device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the image compression method.

[0047] Beneficial effects of the present invention:

[0048] The present invention discloses an image compression system, device and method. The method first collects and analyzes historical data to obtain data analysis information of a reference image. The data analysis coefficient obtained according to the data analysis information can comprehensively measure the compression qualification degree, and the larger the data analysis coefficient is, the higher the compression qualification degree is. Then, a segmentation reference value is obtained according to the qualified reference image, and the image to be compressed is segmented according to the segmentation reference value, so as to ensure the compression qualification of the image segmentation compression. Then, the compressed image is quality tested to obtain quality monitoring information. The quality monitoring coefficient obtained according to the quality monitoring information can comprehensively measure the image compression quality degree, and the larger the quality monitoring coefficient is, the lower the image compression quality degree is. When the image compression quality degree is too low, an abnormal alarm is issued. The system uses intelligent segmentation technology and then separates the compression to achieve efficient image compression while ensuring the quality of the compressed image and improving the perceived quality of the image. The system also performs quality monitoring after compression, which can accurately reflect the quality of the compressed image and provide a reliable basis for adjusting the compression parameters. The system achieves efficient image compression while ensuring the image quality, and achieves a good balance between compression efficiency and image quality. The system is suitable for different types of images and compression requirements and has strong versatility and expansibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below in conjunction with the accompanying drawings.

[0050] Figure 1 It is a principle block diagram of an image compression system in the present invention;

[0051] Figure 2 It is a flow chart of an image compression method in the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Embodiment 1:

[0054] See also Figure 1 As shown, this embodiment is an image compression system, comprising the following modules: a data acquisition module, a data analysis module, an image segmentation module, an image compression module, a compressed image storage module, a quality monitoring module and an abnormal alarm module;

[0055] The data acquisition module is used to obtain the reference image i according to the historical data, obtain the data analysis information of the reference image i, and send the data analysis information to the data analysis module; wherein the data analysis information includes the compression value YS and the time difference value SS;

[0056] The data analysis module is used to obtain a data analysis coefficient SF according to the data analysis information, and send the data analysis coefficient SF to the image segmentation module;

[0057] The image segmentation module is used to obtain a selected reference image according to the data analysis coefficient SF, obtain a segmentation reference value according to the selected reference image, and segment the image to be compressed according to the segmentation reference value to obtain an image block Tj, and send the image block Tj to the image compression module;

[0058] The image compression module is used to compress all the image blocks Tj simultaneously, obtain the compressed image block Yj after the compression is completed, and send the compressed image block Yj to the compressed image storage module;

[0059] The compressed image storage module is used to store the compressed image block Yj, generate a quality monitoring instruction, and send the quality monitoring instruction to the quality monitoring module;

[0060] The quality monitoring module is used to play the compressed image block Yj continuously according to the number after receiving the quality monitoring instruction, obtain the quality monitoring information of the continuous playback process, obtain the quality monitoring coefficient ZL according to the quality monitoring information, and send the quality monitoring coefficient ZL to the abnormal alarm module; wherein the quality monitoring information includes the jamming value KD and the abnormal picture value YH;

[0061] The abnormal alarm module is used to sound a compression abnormality alarm according to the quality monitoring coefficient ZL.

[0062] Embodiment 2:

[0063] See also Figure 2 As shown, this embodiment is an image compression method, comprising the following steps:

[0064] Step 1: The data acquisition module obtains the reference image i according to the historical data, and obtains the data analysis information of the reference image i, wherein the data analysis information includes the compression value YS and the time difference value SS, and sends the data analysis information to the data analysis module;

[0065] Step 2: The data analysis module obtains the data analysis coefficient SF according to the data analysis information, and sends the data analysis coefficient SF to the image segmentation module;

[0066] Step 3: The image segmentation module obtains a selected reference image according to the data analysis coefficient SF, obtains a segmentation reference value according to the selected reference image, and segments the image to be compressed according to the segmentation reference value to obtain image blocks Tj, and sends the image blocks Tj to the image compression module;

[0067] Step 4: The image compression module compresses all the image blocks Tj simultaneously, obtains the compressed image block Yj after the compression is completed, and sends the compressed image block Yj to the compressed image storage module;

[0068] Step 5: The compressed image storage module stores the compressed image block Yj, generates a quality monitoring instruction, and sends the quality monitoring instruction to the quality monitoring module;

[0069] Step 6: After receiving the quality monitoring instruction, the quality monitoring module plays the compressed image block Yj continuously according to the number, obtains the quality monitoring information of the continuous playback process, wherein the quality monitoring information includes the jamming value KD and the abnormal picture value YH, obtains the quality monitoring coefficient ZL according to the quality monitoring information, and sends the quality monitoring coefficient ZL to the abnormal alarm module;

[0070] Step 7: The abnormal alarm module sounds a compression abnormal alarm according to the quality monitoring coefficient ZL.

[0071] Embodiment 3:

[0072] Based on any of the above embodiments, Embodiment 3 of the present invention is a data acquisition module. The function of the data acquisition module is to obtain data analysis information, wherein the data analysis information includes a compression value YS and a time difference value SS. The specific process is as follows:

[0073] The data acquisition module obtains the disk size of the image to be compressed and marks it as the pre-compression value YZ;

[0074] The data acquisition module obtains all images with the same pre-compression occupation value YZ from the historical data and marks them as reference images i, where i=1, 2, 3, ..., n, where n is a positive integer, n represents the total number of reference images, and i is the number of any reference image;

[0075] The data acquisition module obtains the disk size occupied by the image after compression during the compression process of the reference image i, and marks it as the post-compression value YH, obtains the difference between the pre-compression value YZ and the post-compression value YH, and marks it as the compression value YS;

[0076] The data acquisition module obtains the time taken for the reference image i to be compressed, and marks it as the compression length value YC, obtains the time taken for the image blocks divided from the reference image i to be compressed, and marks it as the block length value KC, obtains the average value of all block length values ​​KC, and marks it as the block mean KJ, obtains the difference between the maximum block length value KC and the minimum block length value KC, and marks it as the long difference CC, quantizes the compression length value YC, the block mean KJ, and the long difference CC, extracts the values ​​of the compression length value YC, the block mean KJ, and the long difference CC, and substitutes them into the formula for calculation. According to the formula The time difference value SS is obtained, where s1, s2 and s3 are respectively the preset proportional coefficients corresponding to the set compression length value YC, the block mean value KJ and the length difference value CC, s1, s2 and s3 satisfy s1+s2+s3=1, 0<s3<s2<s1<1, and s1=0.41, s2=0.33, s3=0.26;

[0077] The data acquisition module sends the compression value YS and the time difference value SS to the data analysis module.

[0078] Embodiment 4:

[0079] Based on any of the above embodiments, Embodiment 4 of the present invention is a data analysis module. The function of the data analysis module is to obtain a data analysis coefficient SF. The specific process is as follows:

[0080] The data analysis module quantifies the compression value YS and the time difference value SS, extracts the values ​​of the compression value YS and the time difference value SS, and substitutes them into the formula for calculation. The data analysis coefficient SF is obtained, where e is a mathematical constant, ε is a preset error adjustment factor, ε=0.938, α1 and α2 are preset weight factors corresponding to the set compression value YS and time difference value SS, α1 and α2 satisfy α1>α2>1.32, α1=2.13, α2=1.69;

[0081] The data analysis module sends the data analysis coefficient SF to the image segmentation module.

[0082] Embodiment 5:

[0083] Based on any of the above embodiments, Embodiment 5 of the present invention is an image segmentation module. The function of the image segmentation module is to obtain an image block Tj. The specific process is as follows:

[0084] The image segmentation module compares the data analysis coefficient SF with the preset data analysis threshold SFy:

[0085] If the data analysis coefficient SF ≥ the data analysis threshold SFy, the reference image i is marked as a compression qualified image;

[0086] The image segmentation module randomly extracts a preset number of compressed qualified images from all the compressed qualified images, marks them as selected reference images, obtains the segmentation byte value when the selected reference image is segmented, obtains the average value of all the segmentation byte values, and marks it as the segmentation reference value;

[0087] The image segmentation module segments the image to be compressed according to the segmentation reference value, and obtains image blocks Tj from front to back according to the front and back positions in the image to be compressed, where j=1, 2, 3, ..., m, where m is a positive integer, m represents the total number of image blocks, j is the number of any image block, and the image block Tj is sent to the image compression module.

[0088] Embodiment 6:

[0089] Based on any of the above embodiments, Embodiment 6 of the present invention is an image compression module. The function of the image compression module is to obtain a compressed image block Yj. The specific process is as follows:

[0090] The image compression module compresses all the image blocks Tj simultaneously, obtains the compressed image block Yj after the compression is completed, and sends the compressed image block Yj to the compressed image storage module.

[0091] Embodiment 7:

[0092] Based on any of the above embodiments, Embodiment 7 of the present invention is a compressed image storage module. The function of the compressed image storage module is to generate a quality monitoring instruction. The specific process is as follows:

[0093] The compressed image storage module stores the compressed image block Yj, generates a quality monitoring instruction, and sends the quality monitoring instruction to the quality monitoring module.

[0094] Embodiment 8:

[0095] Based on any of the above embodiments, Embodiment 8 of the present invention is a quality monitoring module. The function of the quality monitoring module is to obtain the quality monitoring coefficient ZL. The specific process is as follows:

[0096] After receiving the quality monitoring instruction, the quality monitoring module plays the compressed image blocks Yj continuously according to the number, wherein the continuous play means that after the compressed image block Y1 is played, the compressed image block Y2 starts to be played until all the compressed image blocks Yj are played, and the playback is performed according to the preset playback multiple;

[0097] The quality monitoring module obtains the number of freezes and abnormal screens during the continuous playback of the compressed image block Yj, and marks them as freeze values ​​KD and abnormal screen values ​​YH, respectively, where the abnormal screens include black screens, flowery screens, and flashing screens;

[0098] The quality monitoring module quantifies the jamming value KD and the abnormal picture value YH, extracts the values ​​of the jamming value KD and the abnormal picture value YH, and substitutes them into the formula for calculation. The quality monitoring coefficient ZL is obtained, where μ is the preset error adjustment factor, μ=1.112, z1 and z2 are the preset proportional coefficients corresponding to the set jam value KD and the abnormal picture value YH, respectively, z1 and z2 satisfy z1+z2=1, 0<z1<z2<1, and z1=0.43 and z2=0.57;

[0099] The quality monitoring module sends the quality monitoring coefficient ZL to the abnormal alarm module.

[0100] Embodiment 9:

[0101] Based on any of the above embodiments, Embodiment 9 of the present invention is an abnormal alarm module. The function of the abnormal alarm module is to sound a compression abnormal alarm. The specific process is as follows:

[0102] The abnormal alarm module compares the quality monitoring coefficient ZL with the preset quality monitoring threshold ZLy:

[0103] If the quality monitoring coefficient ZL ≥ the quality monitoring threshold ZLy, a compression abnormality alarm sounds.

[0104] Based on Examples 1-9, the working principle of the present invention is as follows:

[0105] The present invention provides an image compression system, device and method. A reference image is obtained according to historical data through a data acquisition module, and data analysis information of the reference image is obtained, wherein the data analysis information includes a compression value and a time difference value. A data analysis coefficient is obtained according to the data analysis information through a data analysis module. A selected reference image is obtained according to the data analysis coefficient through an image segmentation module, and a segmentation reference value is obtained according to the selected reference image. The image to be compressed is segmented according to the segmentation reference value to obtain image blocks. All image blocks are compressed simultaneously through an image compression module to obtain compressed image blocks after compression. The compressed image blocks are stored through a compressed image storage module, and a quality monitoring instruction is generated at the same time. After receiving the quality monitoring instruction, the quality monitoring module plays the compressed image blocks continuously according to the number to obtain quality monitoring information of the continuous playback process, wherein the quality monitoring information includes a stutter value and a different picture value. A quality monitoring coefficient is obtained according to the quality monitoring information, and a compression abnormality alarm is sounded according to the quality monitoring coefficient through an abnormal alarm module. The method firstly collects and analyzes historical data to obtain data analysis of the reference image. Information, the data analysis coefficient obtained according to the data analysis information can comprehensively measure the compression qualification degree, and the larger the data analysis coefficient is, the higher the compression qualification degree is. Then, the segmentation reference value is obtained according to the qualified reference image, and the image to be compressed is segmented according to the segmentation reference value, which can ensure the compression qualification of the image segmentation compression. Then, the compressed image is quality tested to obtain quality monitoring information. The quality monitoring coefficient obtained according to the quality monitoring information can comprehensively measure the image compression quality degree, and the larger the quality monitoring coefficient is, the lower the image compression quality degree is. When the image compression quality degree is too low, an abnormal alarm is issued; the system uses intelligent segmentation technology and then separates the compression to achieve efficient image compression while ensuring the quality of the compressed image and improving the perceived quality of the image. It also performs quality monitoring after compression, which can accurately reflect the quality of the compressed image and provide a reliable basis for adjusting the compression parameters. The system achieves efficient image compression while ensuring image quality, and achieves a good balance between compression efficiency and image quality. It is suitable for different types of images and compression requirements and has strong versatility and extensibility.

[0106] It should be further explained that the above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0107] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0108] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined in this application, they shall all fall within the protection scope of the present invention.

Claims

1. An image compression system, characterized in that: include: The data acquisition module is used to obtain the reference image i according to the historical data, obtain the data analysis information of the reference image i, and send the data analysis information to the data analysis module; wherein the data analysis information includes the compression value YS and the time difference value SS; The specific process of the data acquisition module obtaining the compression value YS is as follows: Get the disk size of the image to be compressed and mark it as the pre-compression value YZ; Obtain all images with the same pre-compression occupation value YZ from historical data and mark them as reference images i; Obtain the disk size of the image after compression during the compression process of the reference image i, and mark it as the post-compression value YH, obtain the difference between the pre-compression value YZ and the post-compression value YH, and mark it as the compression value YS; The specific process of the data acquisition module obtaining the time difference value SS is as follows: Get the time length of the reference image i to be compressed, and mark it as the compression length value YC, get the time length of the image blocks divided by the reference image i to be compressed, and mark it as the block length value KC, get the average value of all block length values ​​KC, and mark it as the block mean value KJ, get the difference between the maximum block length value KC and the minimum block length value KC, and mark it as the long difference value CC, quantize the compression length value YC, the block mean KJ and the long difference CC, according to the formula The time difference value SS is obtained, wherein s1, s2 and s3 are respectively the preset proportional coefficients corresponding to the set compression length value YC, the block mean value KJ and the length difference value CC; A data analysis module, used for obtaining a data analysis coefficient SF according to the data analysis information, and sending the data analysis coefficient SF to the image segmentation module; The specific process of the data analysis module obtaining the data analysis coefficient SF is as follows: The compression value YS and the time difference value SS are quantized according to the formula The data analysis coefficient SF is obtained, wherein e is a mathematical constant, ε is a preset error adjustment factor, and α1 and α2 are preset weight factors corresponding to the set compression value YS and the time difference value SS respectively; Send the data analysis coefficient SF to the image segmentation module; An image segmentation module, used to obtain a selected reference image according to the data analysis coefficient SF, obtain a segmentation reference value according to the selected reference image, and segment the image to be compressed according to the segmentation reference value to obtain image blocks Tj, and send the image blocks Tj to the image compression module; An image compression module is used to compress all image blocks Tj simultaneously, obtain compressed image blocks Yj after compression, and send the compressed image blocks Yj to the compressed image storage module; A compressed image storage module, used for storing the compressed image block Yj; The quality monitoring module is used to play the compressed image block Yj continuously according to the number after receiving the quality monitoring instruction, obtain the quality monitoring information of the continuous playback process, obtain the quality monitoring coefficient ZL according to the quality monitoring information, and send the quality monitoring coefficient ZL to the abnormal alarm module; wherein the quality monitoring information includes the jamming value KD and the abnormal picture value YH; The specific process of the quality monitoring module obtaining the quality monitoring coefficient ZL is as follows: After receiving the quality monitoring instruction, the compressed image blocks Yj are played continuously according to the numbers; Obtain the number of freezes and abnormal images during the continuous playback of the compressed image block Yj, and mark them as freeze value KD and abnormal image value YH respectively; The jamming value KD and the abnormal picture value YH are quantified according to the formula The quality monitoring coefficient ZL is obtained, where μ is the preset error adjustment factor, and z1 and z2 are the preset proportional coefficients corresponding to the set stutter value KD and the abnormal picture value YH respectively; The quality monitoring coefficient ZL is sent to the abnormal alarm module.

2. An image compression system according to claim 1, characterized in that: The specific process of the image segmentation module obtaining the image block Tj is as follows: Compare the data analysis coefficient SF with the preset data analysis threshold SFy: If the data analysis coefficient SF ≥ the data analysis threshold SFy, the reference image i is marked as a compression qualified image; Randomly extracting a preset number of compressed qualified images from all compressed qualified images, marking them as selected reference images, obtaining the segmentation byte value when the selected reference image is segmented, and obtaining the average value of all segmentation byte values, and marking it as the segmentation reference value; The image to be compressed is segmented according to the segmentation reference value, and image blocks Tj are obtained from front to back according to the front and back positions in the image to be compressed, and the image blocks Tj are sent to the image compression module.

3. An image compression system according to claim 1, characterized in that: Also includes: The abnormal alarm module is used to sound a compression abnormality alarm according to the quality monitoring coefficient ZL.

4. An image compression system according to claim 3, characterized in that: The specific process of the abnormal alarm module sounding the compression abnormal alarm is as follows: Compare the quality monitoring coefficient ZL with the preset quality monitoring threshold ZLy: If the quality monitoring coefficient ZL ≥ the quality monitoring threshold ZLy, a compression abnormality alarm sounds.

5. An image compression method applied to the image compression system according to any one of claims 1 to 4, characterized in that: The following steps are involved: Step 1: The data acquisition module obtains the reference image i according to the historical data, and obtains the data analysis information of the reference image i, wherein the data analysis information includes the compression value YS and the time difference value SS, and sends the data analysis information to the data analysis module; Step 2: The data analysis module obtains the data analysis coefficient SF according to the data analysis information, and sends the data analysis coefficient SF to the image segmentation module; Step 3: The image segmentation module obtains a selected reference image according to the data analysis coefficient SF, obtains a segmentation reference value according to the selected reference image, and segments the image to be compressed according to the segmentation reference value to obtain image blocks Tj, and sends the image blocks Tj to the image compression module; Step 4: The image compression module compresses all the image blocks Tj simultaneously, obtains the compressed image block Yj after the compression is completed, and sends the compressed image block Yj to the compressed image storage module; Step 5: The compressed image storage module stores the compressed image block Yj, generates a quality monitoring instruction, and sends the quality monitoring instruction to the quality monitoring module; Step 6: After receiving the quality monitoring instruction, the quality monitoring module plays the compressed image block Yj continuously according to the number, obtains the quality monitoring information of the continuous playback process, wherein the quality monitoring information includes the jamming value KD and the abnormal picture value YH, obtains the quality monitoring coefficient ZL according to the quality monitoring information, and sends the quality monitoring coefficient ZL to the abnormal alarm module; Step 7: The abnormal alarm module sounds a compression abnormal alarm according to the quality monitoring coefficient ZL.

6. An image compression device for executing the image compression method according to claim 5, characterized in that: The system comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the image compression method.

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