Video decompression method and device

Abstract

The invention provides a video decompression method and device. The video decompression method comprises the following steps: acquiring a to-be-compressed original video file; processing the original video file by using multi-segment broken line mapping; performing offset quantization processing on the video image after bit width reduction to obtain a compressed video file; the decompression method comprises the following steps: acquiring a plurality of continuous compressed video images from a compressed video file; performing motion estimation on the compressed video image; performing inverse quantization processing on the image after motion estimation to obtain an inverse quantization image; and processing the inverse quantization image by utilizing multi-section broken line mapping to obtain a decompressed video file. Through multi-segment broken line mapping and offset quantization processing, the bit width of the image can be reduced through simple operation to complete compression; the compressed image is aligned through motion estimation, and the compressed image can be recovered through simple operation through inverse quantization processing and multi-segment broken line mapping, so that the problems of complex algorithm, large hardware resource occupation and low efficiency in the existing video compression and decompression process are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of video processing, and in particular to a video decompression method and device. Background Art

[0002] Since complete video files are usually large, they require more storage space; at the same time, since the amount of complete video data is large, the efficiency of transmitting video data is low and the cost is also high. Therefore, in order to reduce the storage space occupied, improve the efficiency of transmitting video data, and reduce the cost, video files are usually compressed first, and then stored or transmitted. When the video content needs to be extracted, the compressed video file is decompressed.

[0003] In order to ensure the quality of the decompressed video, the existing video compression methods usually maximize the compression rate without significantly sacrificing the video quality. Although many commonly used complex video compression methods can greatly compress the file size of the video, they require more computing resources, so the existing video compression methods usually need to be calculated offline.

[0004] However, more and more application scenarios require real-time video compression and transmission. In these application scenarios, the computing power and storage capacity of the compression process are limited. Existing video compression methods cannot meet the needs of real-time compression. Therefore, it is necessary to provide a video compression method with a simple algorithm and easy hardware implementation. In addition, the existing decompression method corresponding to the video compression method is also relatively complex, which is not conducive to improving the efficiency of decompression and reducing the cost. Summary of the invention

[0005] The purpose of the present invention is to provide a video decompression method and device to solve the problems of complex algorithms, large hardware resource occupation and low efficiency in existing video compression and decompression processes.

[0006] In order to solve the above technical problems, the present invention provides a video compression method, comprising: Get the original video file to be compressed; The original video file is processed by using multi-segment polyline mapping to reduce the bit width of the video image in the original video file; The video image with reduced bit width is subjected to offset quantization processing to obtain a compressed video file.

[0007] Optionally, in the video compression method, the method of processing the original video file using multi-segment polyline mapping includes: According to the first compression factor, the horizontal coordinates and the vertical coordinates of the polyline endpoints are set; The video image in the original video file is processed using the polyline endpoints, where the processing formula is:

[0008]

[0009] in, Indicates the horizontal coordinate of the polyline endpoint. Represents the ordinate of the endpoint of the polyline, i=1,2,…,n; Represents the pixel points of the video image after the bit width is reduced. Represents the pixels of the original video image.

[0010] Optionally, in the video compression method, the method of performing offset quantization processing on the video image after the bit width is reduced includes: According to the first compression factor and the second compression factor, an offset weight is obtained, wherein the calculation formula of the offset weight is:

[0011] in, represents the first compression factor, represents the second compression factor; According to the offset weight and the offset transformation period, the offset of the video image is obtained, wherein the calculation formula of the offset is:

[0012] in, Indicates the image number of the video image in the original video file, i=1,2,…,p, p indicates the total number of video images in the original video file; T is the offset transformation period, mod() indicates the remainder operation, and round() indicates the integer operation; The video image is subjected to offset quantization processing using the offset and the offset weight to obtain a compressed video image, wherein the formula used for the offset quantization processing is:

[0013] Among them, IC represents compressed video image.

[0014] Optionally, in the video compression method, the value range of the offset transformation period is 9~16.

[0015] In order to solve the above technical problems, the present invention also provides a video decompression method, comprising: Obtaining a number of continuous compressed video images from a compressed video file; Perform motion estimation on compressed video images; Performing inverse quantization processing on the image after motion estimation to obtain an inverse quantized image; The dequantized image is processed using multi-segment polyline mapping to obtain a decompressed video file.

[0016] Optionally, in the video decompression method, the method for performing motion estimation on the compressed video image includes: Perform mean pooling processing on all the compressed video images obtained; The first compressed video image after mean pooling is used as a reference image; Taking the reference image as a benchmark, motion estimation is performed on other compressed video images after mean pooling processing to obtain a motion estimation result; Perform nearest neighbor upsampling on the motion estimation result to obtain a full-resolution motion estimation result; The full-resolution motion estimation result is used to perform motion compensation on the remaining compressed video images except the reference image to obtain a motion compensated image.

[0017] Optionally, in the video decompression method, the motion estimation algorithm is a block matching method or an optical flow method.

[0018] Optionally, in the video decompression method, the method of performing inverse quantization processing on the image after motion estimation includes: The quantization interval of the reference image and the offset quantization interval of the image after motion estimation are calculated, wherein the calculation formula of the quantization interval of the reference image is:

[0019]

[0020] The calculation formula of the offset quantization interval of the image after motion estimation is:

[0021]

[0022] in, represents the reference image, represents the image after motion compensation; represents the offset weight; T is the offset transformation period; Indicates the image number of the compressed video image in the compressed video file, i=1,2,…,q, q represents the total number of compressed video images obtained from the compressed video file; mod() represents the remainder operation, and round() represents the integer operation; According to the quantization interval of the reference image and the offset quantization interval of the image after motion estimation, the mask image of the quantization interval is updated, wherein the update formula of the mask image is:

[0023] According to the updated mask image, the offset quantization interval of the image is updated to gradually narrow the upper and lower limits of the offset quantization interval; According to the updated offset quantization interval, the inverse quantized image is calculated, where the calculation formula is:

[0024] in, Indicates the upper limit of the updated offset quantization interval, Indicates the lower limit of the updated offset quantization interval.

[0025] Optionally, in the video decompression method, the dequantized image is processed using multi-segment broken line mapping, wherein the processing formula is:

[0026]

[0027] in, Indicates the horizontal coordinate of the polyline endpoint. Represents the ordinate of the endpoint of the polyline, i=1,2,…,n; Represents the pixel points of the decompressed video image, Represents the pixel of the dequantized image.

[0028] In order to solve the above technical problems, the present invention also provides a video compression device, including a memory, a processor and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, it executes the video compression method described in any one of the above items.

[0029] In order to solve the above technical problems, the present invention also provides a video decompression device, comprising a memory, a processor and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, it executes the video decompression method as described in any one of the above items.

[0030] The video decompression method and device provided by the present invention include: obtaining an original video file to be compressed; processing the original video file using multi-segment broken line mapping to reduce the bit width of the video image in the original video file; performing offset quantization processing on the video image after the bit width is reduced to obtain a compressed video file; the decompression method includes: obtaining a plurality of continuous compressed video images from the compressed video file; performing motion estimation on the compressed video image; performing inverse quantization processing on the image after motion estimation to obtain an inverse quantized image; and processing the inverse quantized image using multi-segment broken line mapping to obtain a decompressed video file. The multi-segment broken line mapping and offset quantization processing can reduce the image bit width through simple operations to complete compression; the compressed image can be aligned through motion estimation and the compressed image can be restored through simple operations through inverse quantization processing and multi-segment broken line mapping, thereby solving the problems of complex algorithms, large hardware resource occupation and low efficiency in the existing video compression and decompression process. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A flowchart of the video compression method provided in this embodiment; Figure 2 This is a flow chart of the video decompression method provided in this embodiment. DETAILED DESCRIPTION

[0032] The video decompression method and device proposed in the present invention are further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the accompanying drawings are in a very simplified form and use non-precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In addition, the structure shown in the accompanying drawings is often a part of the actual structure. In particular, the emphasis of each accompanying drawing is different, and sometimes different proportions are used.

[0033] It should be noted that the terms "first", "second", etc. in the specification, claims and drawings of the present invention are used to distinguish similar objects in order to describe the embodiments of the present invention, rather than to describe a specific order or sequence. It should be understood that the structures used in this way can be interchanged under appropriate circumstances. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] This embodiment provides a video compression method, such as Figure 1 As shown, including: A1, obtaining the original video file to be compressed; A2, using multi-segment polyline mapping to process the original video file to reduce the bit width of the video image in the original video file; A3, performing offset quantization processing on the video image after the bit width is reduced to obtain a compressed video file.

[0035] The video compression method provided in this embodiment compresses the bit width of the image for the first time through multi-segment broken line mapping, and reduces the image bit width for the second time by adding an offset and quantizing the image, thereby efficiently completing the compression of the video file through simple operations, which not only reduces the computational complexity, but also reduces the occupation of hardware resources, thereby solving the problems of complex algorithms, large occupation of hardware resources and low efficiency in the existing video compression process.

[0036] Specifically, in this embodiment, in step A1, an original video file to be compressed is obtained. The original video file contains a plurality of continuous original video images, thereby forming a video. The format of the original video image can be an image in GRBG Bayer format.

[0037] Furthermore, in this embodiment, in step A2, the method of processing the original video file using multi-segment polyline mapping to reduce the bit width of the video image in the original video file includes: A21, setting the horizontal coordinates and vertical coordinates of the endpoints of the polyline according to the first compression factor.

[0038] Specifically, in this embodiment, according to the principle of multi-segment polyline mapping, the horizontal coordinate x can represent the original video image, and the vertical coordinate y can represent the mapped video image. In order to reduce the bit width of the video image, the vertical coordinate y can be set to k1bit, that is, the bit width of the mapped video image is k1bit, where k1 is the first compression factor.

[0039] In practical applications, the value of the first compression factor k1 can be reasonably set according to compression requirements to ensure compression effect while achieving better compression efficiency.

[0040] A22, using the polyline endpoints to process the video image in the original video file, wherein the processing formula is:

[0041]

[0042] in, Indicates the horizontal coordinate of the polyline endpoint. Represents the ordinate of the endpoint of the polyline, i=1,2,…,n; Represents the pixel points of the video image after the bit width is reduced. Represents the pixels of the original video image.

[0043] In this way, by traversing all the pixels of the video image, the video image I1 with reduced bit width can be obtained.

[0044] Furthermore, in this embodiment, in step A3, the method of performing offset quantization processing on the video image after the bit width is reduced to obtain a compressed video file includes: A31, obtaining an offset weight according to the first compression factor and the second compression factor, wherein a calculation formula for the offset weight is:

[0045] in, represents the first compression factor, Represents the second compression factor. Similar to the first compression factor, the second compression factor also represents the bit width of the processed video image.

[0046] A32, obtaining an offset of the video image according to the offset weight and the offset transformation period, wherein the calculation formula of the offset is:

[0047] in, It represents the image number of the video image in the original video file, i=1,2,…,p, where p represents the total number of video images in the original video file; T is the offset transformation period, mod() represents the remainder operation, and round() represents the integer operation.

[0048] In practical applications, the value range of the offset transformation period T is 9~16.

[0049] Considering that there will be quantization error during quantization, the quantization error is , where N represents the quantized bit. When multiple quantizations are performed, the accumulated quantization error will be large, thereby affecting the accuracy of the quantization result. Therefore, in this embodiment, an offset is added to the data each time the quantization is performed to reduce the quantization error, thereby ensuring that the quantized result and the original value can maintain a certain accuracy.

[0050] A33, performing offset quantization processing on the video image using the offset and the offset weight to obtain a compressed video image, wherein the formula used for the offset quantization processing is:

[0051] Among them, IC represents compressed video image.

[0052] Taking into account that the pixel values ​​between consecutive frames in a video do not change much in most cases, adding different offsets to the video images of consecutive frames in the video has an effect similar to quantizing an image after adding offsets multiple times. This can greatly save the amount of computation, thereby effectively improving the efficiency of video compression.

[0053] Corresponding to the above-mentioned video compression method, this embodiment also proposes a video decompression method, such as Figure 2 As shown, including: B1, obtaining a plurality of continuous compressed video images from the compressed video file; B2, motion estimation for compressed video images; B3, performing inverse quantization processing on the image after motion estimation to obtain an inverse quantized image; B4, using multi-segment polyline mapping to process the dequantized image to obtain a decompressed video file.

[0054] The video decompression method provided in this embodiment aligns multiple compressed images through motion estimation, calculates a more accurate quantization interval dequantized image through the offset of the compression process, and restores the compressed image through multi-segment broken line mapping, thereby efficiently completing the decompression of the compressed video file through simple operations, which not only reduces the computational complexity, but also reduces the occupation of hardware resources, thereby solving the problems of complex algorithms, large occupation of hardware resources and low efficiency in the existing video decompression process.

[0055] Specifically, in this embodiment, step B1 obtains a plurality of continuous compressed video images from a compressed video file. The compressed video file contains a plurality of continuous compressed video images, thereby constituting a compressed video. The format of the compressed video image may be an image in the GRBG Bayer format. Assuming that m continuous compressed video images are extracted, the extracted m compressed video images may be sequentially recorded as IC1, IC2, ... IC m .

[0056] Furthermore, in this embodiment, step B2, the method for performing motion estimation on the compressed video image includes: B21, perform mean pooling processing on all the compressed video images obtained.

[0057] Specifically, in this embodiment, when the format of the compressed video image is the GRBG Bayer format, the mean pooling process selects a 2×2 convolution kernel, so that the image in the RGB format can be converted into a grayscale image after the mean pooling process, so as to facilitate subsequent motion estimation calculations.

[0058] B22, use the first compressed video image after mean pooling as a reference image.

[0059] In order to facilitate the distinction between the compressed video images, in this embodiment, the compressed video image after the mean pooling process is still recorded as IC, that is, IC1 (the first compressed video image after the mean pooling process) is used as a reference image.

[0060] B23, taking the reference image as a benchmark, performing motion estimation on other compressed video images after mean pooling processing to obtain a motion estimation result.

[0061] Specifically, the motion estimation algorithm can be a block matching method or an optical flow method, etc. The specific implementation process of the motion estimation algorithm is well known to those skilled in the art, and this application will not go into details. The obtained motion estimation results are recorded as dx and dy, where dx represents the motion vector of each pixel in the compressed video image in the x direction, and dy represents the motion vector of each pixel in the compressed video image in the y direction. Since a 2×2 convolution kernel is used in the mean pooling process, the resolution of the motion estimation results dx and dy obtained at this time is 1 / 4 of the resolution of the original compressed video image.

[0062] B24, perform nearest neighbor upsampling on the motion estimation result to obtain a full-resolution motion estimation result.

[0063] Specifically, in this embodiment, the motion estimation results dx and dy (1 / 4 resolution) obtained in step B23 are multiplied by 2 and then up-sampled to obtain full-resolution motion estimation results dx' and dy'.

[0064] B25, using the full-resolution motion estimation result, motion compensation is performed on the remaining compressed video images except the reference image to obtain a motion compensated image.

[0065] Specifically, in this embodiment, the calculation formula of motion compensation can be expressed as:

[0066] in, represents the image after motion compensation, .

[0067] In this way, through mean pooling processing, motion estimation algorithm and motion compensation, the remaining compressed video images except the reference image are aligned with the reference image, thereby facilitating subsequent inverse quantization processing.

[0068] Furthermore, in this embodiment, in step B3, the method of performing inverse quantization processing on the image after motion estimation to obtain the inverse quantized image includes: B31, calculating the quantization interval of the reference image and the offset quantization interval of the image after motion estimation, wherein the calculation formula of the quantization interval of the reference image is:

[0069]

[0070] The calculation formula of the offset quantization interval of the image after motion estimation is:

[0071]

[0072] Wherein, lb and ub represent the lower limit and upper limit of the quantization interval of the reference image, respectively, and lb' and ub' represent the lower limit and upper limit of the offset quantization interval of the image after motion estimation, respectively; represents the reference image, represents the image after motion compensation; represents the offset weight; T is the offset transformation period; It represents the image number of the compressed video image in the compressed video file, i=1,2,…,q, q represents the total number of compressed video images obtained from the compressed video file; mod() represents the remainder operation, and round() represents the integer operation.

[0073] In practical applications, the offset weight used in decompression is consistent with the offset weight used in the compression process, and the offset weight can be sent together with the compressed file, so that the offset weight used in compression can be directly called in the decompression process. Similarly, the offset transformation period used in decompression can also be consistent with the offset transformation period used in the compression process, and the offset transformation period can also be sent together with the compressed file, so that the offset transformation period used in compression can be directly called in the decompression process.

[0074] B32, updating the mask image of the quantization interval according to the quantization interval of the reference image and the offset quantization interval of the image after motion estimation, wherein the updating formula of the mask image is:

[0075] The mask image is used to mark the pixel positions in the image that can update the upper and lower limits of the offset quantization interval. From the above formula, it can be seen that when the larger value between the lower limit value of the quantization interval and the lower limit value of the offset quantization interval is greater than the smaller value between the upper limit value of the current quantization interval and the upper limit value of the offset quantization interval, it indicates that there is a problem with the motion estimation result of the current pixel point, so the upper and lower limits of the offset quantization interval of the point are not updated; only when the larger value between the lower limit value of the quantization interval and the lower limit value of the offset quantization interval is less than the smaller value between the upper limit value of the current quantization interval and the upper limit value of the offset quantization interval, it will be marked in the mask image, so as to update the offset quantization interval of the pixel point corresponding to the marked position.

[0076] B33, updating the offset quantization interval of the image according to the updated mask image to gradually narrow the upper and lower limits of the offset quantization interval.

[0077] Specifically, in this embodiment, if the new upper limit value is smaller than the current upper limit value, the new upper limit value is used to replace the current upper limit value; the same applies to the lower limit value.

[0078] In this way, the distance between the upper and lower limits of the offset quantization interval can be gradually narrowed, which means that the error of the motion estimation result is getting smaller and smaller.

[0079] B34, calculating the inverse quantized image according to the updated offset quantization interval, wherein the calculation formula is:

[0080] in, Indicates the upper limit of the updated offset quantization interval, Indicates the lower limit of the updated offset quantization interval.

[0081] Furthermore, in this embodiment, in step B4, the inverse quantized image is processed using multi-segment polyline mapping to obtain a decompressed video file, wherein the processing formula is:

[0082]

[0083] in, Indicates the horizontal coordinate of the polyline endpoint. Represents the ordinate of the endpoint of the polyline, i=1,2,…,n; Represents the pixel points of the decompressed video image, Represents the pixel of the dequantized image.

[0084] This step is equivalent to the inverse operation of step A2 in the compression process, thereby achieving decompression of the compressed video.

[0085] The decompression method provided in this embodiment, in conjunction with the compression method, can achieve efficient compression and decompression of video files with less computational effort, and can ensure the quality of the decompressed video files.

[0086] This embodiment also provides a video compression device, including a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the video compression method described above is executed.

[0087] Furthermore, this embodiment further provides a video decompression device, comprising a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the video decompression method as described above is executed.

[0088] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other. In addition, the different parts between the various embodiments can also be used in combination with each other, and the present invention is not limited to this.

[0089] The video decompression method and device provided in this embodiment include: the compression method includes: obtaining the original video file to be compressed; processing the original video file using multi-segment broken line mapping to reduce the bit width of the video image in the original video file; performing offset quantization processing on the video image after the bit width is reduced to obtain a compressed video file; the decompression method includes: obtaining a number of continuous compressed video images from the compressed video file; performing motion estimation on the compressed video image; performing inverse quantization processing on the image after motion estimation to obtain an inverse quantized image; and processing the inverse quantized image using multi-segment broken line mapping to obtain a decompressed video file. The multi-segment broken line mapping and offset quantization processing can reduce the image bit width through simple operations to complete compression; the compressed image can be aligned through motion estimation and the compressed image can be restored through simple operations through inverse quantization processing and multi-segment broken line mapping, which solves the problems of complex algorithms, large hardware resource usage and low efficiency in the existing video compression and decompression process.

[0090] The above description is only a description of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any changes or modifications made by a person skilled in the art in the field of the present invention based on the above disclosure shall fall within the scope of protection of the claims.

Claims

1. A video compression method, characterized in that: include: Get the original video file to be compressed; The original video file is processed by using multi-segment polyline mapping to reduce the bit width of the video image in the original video file; The video image with reduced bit width is subjected to offset quantization processing to obtain a compressed video file.

2. The video compression method according to claim 1, characterized in that: The method for processing the original video file using multi-segment polyline mapping comprises: According to the first compression factor, the horizontal coordinates and the vertical coordinates of the polyline endpoints are set; The video image in the original video file is processed using the polyline endpoints, where the processing formula is: in, Indicates the horizontal coordinate of the polyline endpoint. Represents the ordinate of the endpoint of the polyline, i=1,2,…,n; Represents the pixel points of the video image after the bit width is reduced. Represents the pixels of the original video image.

3. The video compression method according to claim 2, characterized in that: The method for performing offset quantization processing on the video image after the bit width is reduced comprises: According to the first compression factor and the second compression factor, an offset weight is obtained, wherein the calculation formula of the offset weight is: in, represents the first compression factor, represents the second compression factor; According to the offset weight and the offset transformation period, the offset of the video image is obtained, wherein the calculation formula of the offset is: in, Indicates the image number of the video image in the original video file, i=1,2,…,p, p indicates the total number of video images in the original video file; T is the offset transformation period, mod() indicates the remainder operation, and round() indicates the integer operation; The video image is subjected to offset quantization processing using the offset and the offset weight to obtain a compressed video image, wherein the formula used for the offset quantization processing is: Among them, IC represents compressed video image.

4. The video compression method according to claim 3, characterized in that: The value range of the offset transformation period is 9~16.

5. A video decompression method, characterized in that: include: Obtaining a number of continuous compressed video images from a compressed video file; Perform motion estimation on compressed video images; Performing inverse quantization processing on the image after motion estimation to obtain an inverse quantized image; The dequantized image is processed using multi-segment polyline mapping to obtain a decompressed video file.

6. The video decompression method according to claim 5, characterized in that: The method for performing motion estimation on a compressed video image comprises: Perform mean pooling processing on all the compressed video images obtained; The first compressed video image after mean pooling is used as a reference image; Taking the reference image as a benchmark, motion estimation is performed on other compressed video images after mean pooling processing to obtain a motion estimation result; Perform nearest neighbor upsampling on the motion estimation result to obtain a full-resolution motion estimation result; The full-resolution motion estimation result is used to perform motion compensation on the remaining compressed video images except the reference image to obtain a motion compensated image.

7. The video decompression method according to claim 6, characterized in that: The motion estimation algorithm is a block matching method or an optical flow method.

8. The video decompression method according to claim 6, characterized in that: The method for performing inverse quantization processing on the image after motion estimation comprises: The quantization interval of the reference image and the offset quantization interval of the image after motion estimation are calculated, wherein the calculation formula of the quantization interval of the reference image is: The calculation formula of the offset quantization interval of the image after motion estimation is: in, represents the reference image, represents the image after motion compensation; represents the offset weight; T is the offset transformation period; Indicates the image number of the compressed video image in the compressed video file, i=1,2,…,q, q represents the total number of compressed video images obtained from the compressed video file; mod() represents the remainder operation, and round() represents the integer operation; According to the quantization interval of the reference image and the offset quantization interval of the image after motion estimation, the mask image of the quantization interval is updated, wherein the update formula of the mask image is: According to the updated mask image, the offset quantization interval of the image is updated to gradually narrow the upper and lower limits of the offset quantization interval; According to the updated offset quantization interval, the inverse quantized image is calculated, where the calculation formula is: in, Indicates the upper limit of the updated offset quantization interval, Indicates the lower limit of the updated offset quantization interval.

9. The video decompression method according to claim 6, characterized in that: The dequantized image is processed by using multi-segment broken line mapping, wherein the processing formula is: in, Indicates the horizontal coordinate of the polyline endpoint. Represents the ordinate of the endpoint of the polyline, i=1,2,…,n; Represents the pixel points of the decompressed video image, Represents the pixel of the dequantized image.

10. A video compression device, characterized in that: It comprises a memory, a processor and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the video compression method according to any one of claims 1 to 4 is executed.

11. A video decompression device, characterized in that: It comprises a memory, a processor and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the video decompression method as described in any one of claims 5 to 9 is executed.

Images