CN115396670B - Image data compression method for local processing - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000013144 data compression Methods 0.000 title claims abstract description 18
- 238000012545 processing Methods 0.000 title abstract description 12
- 238000007906 compression Methods 0.000 claims abstract description 63
- 230000006835 compression Effects 0.000 claims abstract description 63
- 230000000694 effects Effects 0.000 abstract description 5
- 238000005516 engineering process Methods 0.000 abstract description 4
- 238000013459 approach Methods 0.000 abstract description 2
- 238000007781 pre-processing Methods 0.000 abstract description 2
- 230000000903 blocking effect Effects 0.000 abstract 1
- 239000000284 extract Substances 0.000 abstract 1
- 230000005540 biological transmission Effects 0.000 description 7
- 238000004422 calculation algorithm Methods 0.000 description 6
- 238000004088 simulation Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 239000002689 soil Substances 0.000 description 2
- 238000011161 development Methods 0.000 description 1
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- 238000007907 direct compression Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
- H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
- H04N19/12—Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
- H04N19/122—Selection of transform size, e.g. 8x8 or 2x4x8 DCT; Selection of sub-band transforms of varying structure or type
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
- H04N19/423—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation characterised by memory arrangements
Abstract
The invention provides a local processing image data compression method, which extracts the image blocks which are difficult to compress in advance through local processing, compresses the image after proper processing and conceals information, processes the key few image blocks to improve the whole image compression effect, embodies the concept of compressing and concealing after blocking, judging and preprocessing, improves the image data compression performance, and opens up a new technical approach for the practical application of the existing satellite data compression technology.
Description
Technical Field
The invention relates to a data transmission method, in particular to a local processing image data compression method, which belongs to the field of communication (such as data communication technology and the like).
Background
With the development of technology, people have increasingly demanded high-resolution images, and data volume has increasingly become larger, and data compression is imperative.
Data compression is classified into lossy compression and lossless compression methods. The compression ratio of the lossy compression method is larger, but the restored image and the original image after compression have certain information loss, so long as the subjective and objective evaluation index meets the requirement, the application is not affected greatly in practice; the lossless compression method has no information loss between the restored image and the original image after compression, but the compression ratio is extremely small, generally about 2 times, the use situation is limited, and the data transmission is inconvenient. The compression method adopted by the general high-speed data transmission system is a lossy method, and for images, the general peak signal-to-noise ratio (PSNR) should reach more than 30dB, so that the effect is relatively good.
There are many current image data compression methods, typically JPEG2000. Many algorithms consider the entirety of an image, and the effect of partial performance of a small portion of the image on the compression of the entire large image is great, so that a phenomenon of 'small and large' often exists. Algorithms are related to the nature (or complexity) of the image itself, and do not have good results in all cases. The same compression algorithm varies greatly in compression performance from image to image. For example, when in social removal, nail households are determined, the influence on the removal work is very large, and the removal efficiency is improved. Or when the soil is leveled, stones in the soil are removed first, so that the bulldozer is convenient to construct efficiently. The same is true for satellite image compression.
Disclosure of Invention
The invention solves the technical problems that: the data compression method based on image block processing is provided, the image blocks which are difficult to compress are extracted in advance, the image blocks are compressed after being properly processed, information is embedded, and the local processing improves the compression effect of local images and whole images.
The technical scheme of the invention is as follows: a locally processed image data compression method, comprising:
Dividing an image A with the size of M x N into k image blocks, wherein the size of each block is M x N, and respectively calculating parameters S of each image block, wherein the parameters S are image gradients; m, N, m, n, k are positive integers;
Selecting an image block U from k image blocks, and setting the gray value of the image block U in the original image as a constant X to obtain an image B;
Embedding the image B into the compressed image A to form image compression data D;
Transmitting or storing the image compression data D;
extracting embedded data in the image compressed data D to obtain image block code stream data Q and image compressed data C;
decompressing the image block code stream data Q to obtain a restored image block U, decompressing the image compression data C to obtain a restored image B1 of the image B;
And replacing the corresponding pixels in the restored image B1 by the restored image block U to obtain a restored image A1 of A.
The k= (M x N)/(M x N).
The selection rule of the selected image block U is one of the following:
A. calculating parameters S of all the image blocks, arranging the numerical values of the S in sequence from large to small, and selecting the image block corresponding to the largest S value;
B. Calculating no parameter S, and randomly selecting an image block;
C. the parameter S is not calculated and an image block is selected that contains the region of the object and the texture is complex.
The proportion of the selected image block U to the original image is p, and p=1/k.
The embedding the image B into the compressed image a to form the image compressed data D includes: compressing the image A by R times, compressing the image block U in the compressed image A by R1 times again to form image block code stream data Q, and compressing the image B by R2 times to form image compressed data C; the image block code stream data Q is embedded into the image compression data C to obtain image compression data D of R times the image compression.
R1 is less than or equal to R, R2 is more than or equal to R, and R=1/(p/R1+ (1-p)/R2).
The constant X is the block gray average.
The embedding the image B into the compressed image a to form the image compressed data D, further includes:
Compressing the image A by R times, compressing the image block U in the compressed image A by R1 times again to form image block code stream data Q, and compressing the image B by R times to form image compressed data C; and embedding the image block code stream data Q into the image compression data C to obtain image compression data D which is R times of the image compression, wherein R1 is less than or equal to R.
Compared with the prior art, the invention has the advantages that:
(1) The method of the invention finds out the image blocks which are difficult to compress or the image blocks at the appointed position in the image in advance, then processes the original image appropriately, and compresses the image, thereby improving the compression performance. The compression quality PSNR is improved under the same compression ratio; at the same quality, the compression ratio of the image is improved.
(2) The method of the invention processes the image blocks which are difficult to compress or the image blocks at the appointed position with high quality, and embeds the processed image blocks into the compressed data of the processed image, the image blocks can be compressed relatively well without relatively large compression, thereby improving the compression performance of the whole image and simultaneously maintaining the performance of a few key complex images.
(3) The method can be used in combination with a plurality of conventional compression methods, and images with substandard direct compression performance are screened in advance, so that the adaptability of the compression method to different images is improved.
(4) The method opens up a new technical approach for the practical application of satellite data compression technology, and can improve the compression ratio by only carrying out local preprocessing, calculating parameter values, and based on conventional compression and information hiding in advance, thereby obtaining unexpected compression effects.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of a simulated image of the method of the present invention, with the left side being the original image a and the right side being the processed image B.
Detailed Description
As shown in fig. 1 and 2. In order to verify the performance of the algorithm provided herein, an 8-bit gray scale image with the size of 512×512 is adopted as an image in a simulation experiment, the data compression transmission and recovery are carried out by the method of the invention, and the compression method adopted is a JPEG2000 compression algorithm.
The invention relates to a local processing image data compression method, which comprises the following steps:
1) Dividing an image A with the size of M x N into k image blocks, wherein the size of each block is M x N, and respectively calculating parameters S of each small block, wherein the parameters S are image gradients; m, N, M, N, k is a positive integer, k= (M x N)/(M x N); m=512, n=512, m=n=256, k=4;
2) Comparing parameters S of k images, selecting corresponding image blocks from the parameters S, if the parameters S of a certain image block U meet the requirements, independently taking out the image block U, setting the gray value of the image block U in the original image as a constant X, and setting the typical value as the average value of the gray values of the image block U to obtain an image B;
3) Compressing the image A by R times, compressing the image block selected in the step 2) by R1 times to form image block code stream data Q, and compressing the image B by R2 times to form image compressed data C; embedding the image block data Q into the image compression data C to obtain data D which is R times of image compression; the proportion of the selected image blocks to the original image is p, wherein p=1/k; wherein, r1< = R, r2> = R, r=1/(p/r1+ (1-p)/R2);
4) Transmitting or storing the image compression data D; in this embodiment, r=4, 5.
The parameter S is not calculated, and an image block is selected according to the requirement or a preset position, such as a region containing a target, a region with complex texture and the like;
5) Extracting the embedded data in the step D to obtain image block code stream data Q and image compression data C;
6) Decompressing the code stream data Q to obtain a restored image block U, decompressing the image compression data C to obtain a restored image B1 of the image B;
7) And replacing the corresponding pixels in the restored image B1 by the restored image block U to obtain a restored image A1 of A.
The performance of the compression algorithm is measured using a peak signal to Noise Ratio (PSNR) indicator. For an 8bit digital image of size H W, PSNR is defined as follows:
wherein MSE is the mean square error between the original image and the restored image, and the calculation formula is
Here the number x ij of the total number,Representing the pixel values of the original image and the restored image at (i, j), respectively.
TABLE 1 partial simulation results in examples of the invention
The invention provides a novel image compression method, which improves the compression performance and meets the requirements of users. By using the method provided by the invention, the complex key few areas (such as 1/4-1/16) of the original image are selected by carrying out local calculation in advance, then the conventional image overall compression processing is carried out, the transmission is carried out, and the requirement of channel transmission on the image compression ratio is ensured.
Under the experimental image simulation condition, PSNR performance of the image Airplane.bmp and R times of compression cannot meet the requirement, but after the key block U is selected, the PSNR of the whole image compression is obviously improved, and the performance of the image block is also improved. When r=4, 5 times, the PSNR value of the image block increases to 2.7407dB, 2.4895dB with the performance of the remaining portion of the image remaining unchanged; the PSNR values of the remaining portions are increased to 1.9841dB, 1.3790dB, while ensuring that the performance of the image block is not degraded. Similar performance can be achieved for other types of images. If the selected image blocks are complex, the parameters S of all the image blocks are calculated, the values of S are arranged in sequence from large to small, and the image block corresponding to the largest S value is selected, so that the PSNR can be improved by more than 3-5dB when the compression ratio is fixed.
The method can always improve the performance of overall image compression and ensure the image quality of key local areas. The invention provides a local processing image compression method, which solves the technical problem of improving the overall compression performance of an image through local processing through innovation, realizes the organic combination of inheritance and innovation, is convenient for improving the compression performance by utilizing the existing compression chip without changing a compression system, has the characteristic of being easy to realize by software and hardware, has practical value in a satellite image compression transmission system, and can play a role in any other image compression occasion, and the compression ratio can be varied from 4 times to 16 times.
The invention is not described in detail in the field of technical personnel common knowledge.
Claims (4)
1. A locally processed image data compression method, characterized by comprising:
Dividing an image A with the size of M x N into k image blocks, wherein the size of each block is M x N, and respectively calculating parameters S of each image block, wherein the parameters S are image gradients; m, N, m, n, k are positive integers;
Selecting an image block U from k image blocks, and setting the gray value of the image block U in the original image as a constant X to obtain an image B;
Compressing R1 times of the selected image block U to form image block code stream data Q, and compressing R2 times of the image B to form image compressed data C; embedding the image block data Q into the image compression data C to obtain data D which is R times of image compression; the proportion of the selected image blocks to the original image is p, wherein p=1/k; wherein, r1< = R, r2> = R, r=1/(p/r1+ (1-p)/R2);
Transmitting or storing the image compression data D;
extracting embedded data in the image compressed data D to obtain image block code stream data Q and image compressed data C;
decompressing the image block code stream data Q to obtain a restored image block U, decompressing the image compression data C to obtain a restored image B1 of the image B;
And replacing the corresponding pixels in the restored image B1 by the restored image block U to obtain a restored image A1 of A.
2. A locally processed image data compression method as claimed in claim 1 wherein: the k= (M x N)/(M x N).
3. A locally processed image data compression method as claimed in claim 1 wherein: the selection rule of the selected image block U is one of the following:
A. calculating parameters S of all the image blocks, arranging the numerical values of the S in sequence from large to small, and selecting the image block corresponding to the largest S value;
B. Calculating no parameter S, and randomly selecting an image block;
C. the parameter S is not calculated and an image block is selected that contains the region of the object and the texture is complex.
4. A locally processed image data compression method as claimed in claim 1 wherein: the constant X is the block gray average.
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