CN115396670A - Image data compression method for local area processing - Google Patents
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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
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- 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
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Abstract
The invention provides an image data compression method of local area processing, which extracts image blocks which are difficult to compress in advance through the local area processing, compresses and conceals information after proper processing, processes a few key image blocks to improve the overall image compression effect, embodies the idea 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 an image data compression method for local area processing, and belongs to the field of communication (such as data communication technology and the like).
Background
With the development of science and technology, people have greater and greater requirements on high-resolution images and greater data volume, and data compression is imperative.
Data compression is divided into lossy compression and lossless compression methods. The lossy compression method has a large compression ratio, but the compressed recovered image and the original image have certain information loss, and as long as subjective and objective evaluation indexes meet requirements, the lossy compression method has no great influence on application in practice; the lossless compression method has no information loss between the recovered image and the original image after compression, but the compression ratio is particularly small, generally about 2 times, the use occasion is limited, and data transmission is inconvenient. The compression method adopted by the general high-speed data transmission system is mostly a lossy method, and for images, the peak signal-to-noise ratio (PSNR) generally reaches more than 30dB, and the effect is relatively good.
There are many image data compression methods, and JPEG2000 is representative. Many algorithms are considered from the whole image, and the local performance of a small part of the image has great influence on the compression of the whole large image, and the phenomenon of 'loss of size' often exists. The algorithm is related to the characteristics (or complexity) of the image itself, and has good results in no case. The same compression algorithm has a very different compression performance for different images. For example, when the user breaks down in the society, the nail user is determined, the breaking work is greatly influenced, and the breaking efficiency is improved. Or when the land is leveled, stones in the land are removed first, so that the efficient construction of the bulldozer is facilitated. The same is true for satellite image compression.
Disclosure of Invention
The technical problem solved by the invention is as follows: the data compression method based on image block processing overcomes the defects of the prior art, and improves the compression effect of local images and whole images through extracting image blocks which are difficult to compress in advance, compressing and embedding information after proper processing.
The technical scheme of the invention is as follows: a method of compressing locally processed image data, comprising:
dividing an image A with the size of M x N into k image blocks, wherein each image block is M x N in size, and calculating parameters S of each image block respectively, wherein the parameters S are image gradients; m, N, M, N and k are positive integers;
selecting an image block U from the 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 compressed 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, and decompressing the image compressed 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 blocks U to obtain a restored image A1 of A.
The k = (M × N)/(M × N).
The selection rule for selecting the image block U is one of the following rules:
A. calculating parameters S of all image blocks, arranging the numerical values of S from large to small, and selecting the image block corresponding to the maximum S value;
B. randomly selecting an image block without calculating a parameter S;
C. the parameter S is not calculated, and the image block of the area including the target and having a complex texture is selected.
The proportion of the selected image block U in the original image is p, and p =1/k.
The embedding of the image B into the compressed image a to form 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 to form image block code stream data Q, and compressing the image B by R2 times to form image compressed data C; and embedding the image block code stream data Q into the image compressed data C to obtain image compressed data D with R times of image compression.
R1 is not less than R, R2 is not less than R, and R = 1/(p/R1 + (1-p)/R2).
The constant X is the average value of the gray levels of the blocks.
The embedding of the image B into the compressed image a to form compressed image data D further comprises:
compressing the image A by R times, compressing the image block U in the compressed image A by R1 times 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 compressed data C to obtain image compressed data D with R times of 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 block which is difficult to be compressed or the image block at the appointed position in the image in advance, then processes the original image properly, and then compresses the image, thereby improving the compression performance. Under the same compression ratio, the compression quality PSNR is improved; the compression ratio of the image is improved under the same quality.
(2) The method carries out high-quality data processing on image blocks which are difficult to compress or image blocks at specified positions, and embeds the image blocks into compressed data of the processed image, and the image blocks can not be compressed greatly, so that the quality is relatively good, and the performance of a few key complex images is kept while the compression performance of the whole image is improved.
(3) The method can be combined with a plurality of conventional compression methods for use, and images with unqualified 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 the satellite data compression technology, and can improve the compression ratio only by carrying out local preprocessing, calculating parameter values, and based on conventional compression and information hiding in advance, thereby obtaining an unexpected compression effect.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a schematic diagram of an emulated image of the method of the present invention, with an original image A on the left and a processed image B on the right.
Detailed Description
As shown in fig. 1 and 2. In order to verify the performance of the algorithm provided by the invention, 8-bit gray level images with the size of 512 multiplied by 512 are adopted in the images in the simulation experiment, the data compression transmission and recovery are carried out by using the method, and the adopted compression method is 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 image block is M x N, and calculating parameters S of each small block respectively, wherein the parameters S are image gradients; m, N, k being positive integers, k = (M x N)/(M x N); m =512, n =512, M = n =256, k =4;
2) Comparing parameters S of k images, selecting a corresponding image block 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 taking 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 blocks 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 with R times of image compression; the proportion of the selected image blocks in the original image is p, and 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 example, R =4,5.
Selecting image blocks according to requirements or preset positions, such as an area containing a target, an area with complex textures and the like, without calculating a parameter S;
5) Extracting the data embedded in the D to obtain image block code stream data Q and image compressed data C;
6) Decompressing the code stream data Q to obtain a restored image block U, and decompressing the image compressed 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 blocks U to obtain a restored image A1 of A.
The performance of the compression algorithm is measured using Peak Signal to Noise Ratio (PSNR) metrics. 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 recovered image, and the calculation formula is
Where x is ij ,
Respectively representing the pixel values at (i, j) of the original image and the restored image.
Table 1 partial simulation results in the inventive examples
The invention provides a new image compression method, which improves the compression performance and meets the requirements of users. By utilizing the method provided by the invention, local calculation is performed in advance to select a few complex key regions (such as 1/4-1/16) of the original image, then conventional image overall compression processing is performed for transmission, and the requirement of channel transmission on the image compression ratio is ensured.
Under the condition of experimental image simulation, the PSNR performance of an image airplan.bmp cannot meet the requirement during R-time compression, but after a key block U is selected, the integral compression PSNR of the image is obviously improved, and the performance of an image block is also improved. When R =4,5 times, the PSNR value of the image block is improved to 2.7407dB, 2.4895dB under the condition that the performance of the residual part of the image is not reduced; under the condition of ensuring that the performance of the image blocks is not reduced, the PSNR values of the residual parts are improved to 1.9841dB and 1.3790dB. Similar performance can be achieved for other images of the same type. If the selected image blocks are complex, the parameters S of all the image blocks are calculated, the numerical values of S are arranged from large to small, the image block corresponding to the largest S value is selected, the compression ratio is fixed, and the PSNR can be improved by more than 3-5 dB.
The method can always improve the performance of overall image compression and can ensure the image quality of the key local area. The invention provides an image compression method for local processing, which solves the technical problem of how to improve the overall compression performance of an image through local processing by innovation, organically combines inheritance and innovation, is convenient to utilize the existing compression chip, improves the compression performance without changing a compression system, has the characteristic of easy realization of software and hardware, has practical value in a satellite image compression transmission system, and can play a role in any other image compression occasions.
The invention is not described in detail and is within the knowledge of a person skilled in the art.
Claims (8)
1. A method for compressing image data for local area processing, comprising:
dividing an image A with the size of M x N into k image blocks, wherein the size of each image block is M x N, and respectively calculating a parameter S of each image block, wherein the parameter S is an image gradient; m, N, M, N and k are positive integers;
selecting an image block U from the 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 compressed data D;
transmitting or storing 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, and decompressing the image compressed 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 blocks U to obtain a restored image A1 of A.
2. The image data compression method for local area processing according to claim 1, wherein: the k = (M × N)/(M × N).
3. The image data compression method for local area processing according to claim 1, wherein: the selection rule for selecting the image block U is one of the following rules:
A. calculating parameters S of all image blocks, arranging the numerical values of S from large to small, and selecting the image block corresponding to the maximum S value;
B. randomly selecting an image block without calculating a parameter S;
C. the parameter S is not calculated, and the image block of the area including the target and having a complex texture is selected.
4. The image data compression method for local area processing according to claim 1, wherein: the proportion of the selected image block U in the original image is p, and p =1/k.
5. The image data compression method for local area processing according to claim 4, wherein: the embedding of the image B into the compressed image a to form 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 to form image block code stream data Q, and compressing the image B by R2 times to form image compressed data C; and embedding the image block code stream data Q into the image compressed data C to obtain image compressed data D with R times of image compression.
6. The image data compression method for local area processing according to claim 5, wherein: r1 is not less than R, R2 is not less than R, and R = 1/(p/R1 + (1-p)/R2).
7. A method of compressing locally processed image data according to claim 1, further comprising: the constant X is the average value of the gray levels of the blocks.
8. The image data compression method for local area processing according to claim 1, wherein: the embedding of the image B into the compressed image a to form compressed image data D further comprises:
compressing the image A by R times, compressing the image block U in the compressed image A by R1 times 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 compressed data C to obtain image compressed data D with R times of image compression, wherein R1 is less than or equal to R.
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