CN103051900A - Image compression method based on wavelet transform and clonal selection algorithm - Google Patents
Image compression method based on wavelet transform and clonal selection algorithm Download PDFInfo
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Abstract
The invention relates to an image compression method based on wavelet transform and clonal selection algorithm. The image compression method based on the wavelet transform and the clonal selection algorithm comprises the following steps of: 1) an image data acquisition module collects external image information and sends the external image information to a LVDS (low voltage differential signaling) to TTL (transistor-transistor logic) module; 2) the LVDS to TTL module carries out signal transformation to the collected image information; 3) a synchronous FIFO (first in first out) module stores an image signal converted by the LVDS to TTL module to a SDRAM (synchronous dynamic random access memory) image cache module; 4) an FPGA (field programmable gate array) image data compression module carries out compressed encoding processing to pre-processed image information in the SDRAM image cache module; and 5) an image display module displays image information which is coded and compressed again in the FPGA image data compression module. According to the image compression method based on the wavelet transform and the clonal selection algorithm, which is disclosed by the invention, the image compression efficiency is improved, and the coding quality is high.
Description
Technical field
The present invention relates to the digital image compression technical field, particularly a kind of method for compressing image based on wavelet transformation and clonal selection algorithm.
Background technology
Society is the stepped into information epoch, have every day a large amount of information to store, process and transmit with numeral.Wherein one of the most common, most important information is exactly digital picture.Digital image informations such as video telephone, news picture transmission, IntServ digital network, satellite remote sensing, image transmission, picture retrieval, military satellite scouting, public security checking system, commercial television, electronic teaching plays an important role in the every field of social life and national economy.Meanwhile, the enterprises and individuals has proposed more and more higher requirement to storage, transmission and the exchange of image information.Particularly in satellite communication field, along with the raising of satellite remote sensing images resolution, its data volume sharp increase, this has just brought very large difficulty for its storage and transmission.If these image informations are not done suitable processing, transmit timely them, the bandwidth and the time that need all can't be imagined.Based on above reason, the compress technique of Information Compression, especially digital picture has become one of basic fundamental of information age, and is playing the part of important role.
Now, the digital image compression technology is in continuous research and development and the perfect process, realize the effective transmission of image on channel, particularly at this special transmission channel of satellite communication, make compression effectiveness and the compression efficiency of digital picture reach well-content degree, still have a lot of problems to need to solve.So studying new more efficient image compression theory and method has great actual application value.Wavelet transformation has great significance aspect image compression, and one of the key of Wavelet Image Compression and difficult point are to select the suitable Optimum wavelet base of oneself using.Clonal selection algorithm is a kind of Stochastic Optimization Algorithms of simulation biological immune process, and it has very strong ability of searching optimum, and this search capability does not rely on specific solving model.Therefore, can use clonal selection algorithm and select suitable Optimum wavelet base.
Image compression is exactly not have under the prerequisite of obvious distortion, and the message bit pattern of image is transformed into another can be with the expression-form of data volume reduction, referred to as Image Coding.Therefore why image can compressedly encode, and is because exist redundancy in the image information, can realize compression to image by removing redundant information.The coding entity is pixel or block of pixels, eliminating the data relevant redundancy as purpose, consequent JPEG, MPEG-1, MPEG-2, H.261 reaches and H.263 waits coding international standard to be successful.
Wavelet analysis is a milestone on the Fourier analysis development history, is described as " school microscop ".As a kind of multiresolution analysis method, wavelet analysis has good Time-Frequency Localization characteristic, be particularly suitable for also being very beneficial for the progressive transmission of picture signal according to the coding method of human-eye visual characteristic designed image, be considered to one of optimal selection of carrying out the high compression ratio Image Coding.In actual applications, based on the Image Coding of wavelet transformation, all be better than aspect compression ratio and the coding quality traditional based on piece DCT(Discrete Cosine Transform) transition coding.At present, wavelet analysis is widely used in Static and dynamic image compression field, and has become the important step of some image compression international standard (such as JPEG2000, MPEG-4).
Summary of the invention
Technical problem to be solved by this invention provides a kind of method for compressing image based on wavelet transformation and clonal selection algorithm, and this method makes picture compression efficiency high, and coding quality is excellent.
The technical solution adopted for the present invention to solve the technical problems is: a kind of method for compressing image based on wavelet transformation and clonal selection algorithm is provided, comprise that the image data acquiring module, the LVDS that link to each other successively turn TTL module, synchronous FIFO module, image buffer storage module, FPGA image data compression module and image display, described method for compressing image may further comprise the steps:
1) described image data acquiring module gathers external image information and sends it to LVDS and turns the TTL module;
2) described LVDS turns the TTL module and carries out the signal conversion to collecting image information;
3) described synchronous FIFO module stores the picture signal that LVDS turns after the TTL module converts into SDRAM image buffer storage module;
4) described FPGA image data compression module is carried out the compressed encoding processing to the pretreatment image information in the SDRAM image buffer storage module;
5) described image display shows the image information of recompile compression in the FPGA image data compression module.
FPGA image data compression module in the described step 4) comprises IMAQ coding module, sram cache module, wavelet transformation module, clonal selection algorithm module, display control module, and the compressed encoding processing method of described FPGA image data compression module may further comprise the steps
(a) described IMAQ coding module gathers the image information in the SDRAM image buffer storage module and it is buffered in the sram cache module;
(b) described wavelet transformation module is carried out wavelet transformation to the image information that is stored in the sram cache module;
(c) described clonal selection algorithm module is selected image information carry out Optimum wavelet base in the wavelet transformation in the wavelet transformation module, and it is passed in wavelet transformation module and the sram cache module;
(d) described display control module obtains the view data of recompile compression in the sram cache module and it is passed to image display.
Beneficial effect
The present invention relates to a kind of method for compressing image based on wavelet transformation and clonal selection algorithm, the decorrelation of orthogonal wavelet exchange and the global convergence of clonal selection algorithm are applied in the image compression, utilize the global convergence ability of clonal selection algorithm, search globally optimal solution, and improve constringency performance, thereby select suitable Optimum wavelet base, based on the distinctive concurrency of FPGA and flowing water linearity this image compression algorithm is carried out hardware designs, picture compression efficiency is high, all be better than aspect compression ratio and the coding quality traditional based on piece DCT(Discrete Cosine Transform) transition coding.
Description of drawings
Fig. 1 is hardware configuration schematic diagram of the present invention;
Fig. 2 is the inside connection layout of FPGA image data compression module of the present invention.
Embodiment
Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that these embodiment only to be used for explanation the present invention and be not used in and limit the scope of the invention.Should be understood that in addition those skilled in the art can make various changes or modifications the present invention after the content of having read the present invention's instruction, these equivalent form of values fall within the application's appended claims limited range equally.
Shown in Fig. 1-2, the present invention relates to a kind of method for compressing image based on wavelet transformation and clonal selection algorithm, comprise that the image data acquiring module 1, the LVDS that link to each other successively turn TTL module 2, synchronous FIFO module 3, image buffer storage module 4, FPGA image data compression module 5 and image display 6, described method for compressing image may further comprise the steps:
1) described image data acquiring module 1 gathers external image information and sends it to LVDS and turns TTL module 2;
2) described LVDS turns 2 pairs of TTL modules and collects image information and carry out signal conversion;
3) described synchronous FIFO module 3 stores the picture signal that LVDS turns after TTL module 2 is changed into SDRAM image buffer storage module 4;
4) the pretreatment image information in 5 pairs of SDRAM image buffer storages of described FPGA image data compression module module 4 is carried out the compressed encoding processing;
5) image information of recompile compression shows in 6 pairs of FPGA image data compression module 5 of described image display.
FPGA image data compression module 5 in the described step 4) comprises IMAQ coding module 11, sram cache module 7, wavelet transformation module 9, clonal selection algorithm module 8, display control module 10, and the compressed encoding processing method of described FPGA image data compression module 5 may further comprise the steps:
(a) described IMAQ coding module 11 gathers the image information in the SDRAM image buffer storage modules 4 and it is buffered in the sram cache module 7;
(b) image information that is stored in the sram cache module 7 of 9 pairs of described wavelet transformation modules is carried out wavelet transformation;
(c) described clonal selection algorithm module 8 is selected image information carry out Optimum wavelet base in the wavelet transformation in wavelet transformation module 9, and it is passed in wavelet transformation module 9 and the sram cache module 7;
(d) described display control module 10 obtains the view data of recompile compression in the sram cache module 7 and it is passed to image display 6.
First gather external image information by image data acquiring module 1 and send it to LVDS and turn TTL module 2 and carry out the signal conversion, picture signal after will being changed by synchronous FIFO module 3 again stores SDRAM image buffer storage module 4 into, IMAQ coding module 11 in the FPGA image data compression module 5 gathers and is stored in the picture signal in the SDRAM image buffer storage module 4 and sends it to sram cache module 7, the picture signal that 9 pairs of wavelet transformation modules are stored in the sram cache module 7 is carried out the small echo exchange, utilize the global convergence ability of clonal selection algorithm module 8, search globally optimal solution, and improve constringency performance, in wavelet transformation module 9 wavelet transformation processes, select suitable Optimum wavelet base, wavelet transformation module 9 is stored in sram cache module 7 with the view data of recompile compression, and display control module 10 obtains the image information that is stored in the view data in the sram cache module 7 and sends it to 6 pairs of compressions of image display and shows.
Claims (2)
1. method for compressing image based on wavelet transformation and clonal selection algorithm, comprise that the image data acquiring module (1), the LVDS that link to each other successively turn TTL module (2), synchronous FIFO module (3), image buffer storage module (4), FPGA image data compression module (5) and image display (6), it is characterized in that: described method for compressing image may further comprise the steps:
1) described image data acquiring module (1) gathers external image information and sends it to LVDS and turns TTL module (2);
2) described LVDS turns TTL module (2) and carries out the signal conversion to collecting image information;
3) described synchronous FIFO module (3) stores the picture signal that LVDS turns after TTL module (2) is changed into SDRAM image buffer storage module (4);
4) described FPGA image data compression module (5) is carried out the compressed encoding processing to the pretreatment image information in the SDRAM image buffer storage module (4);
5) described image display (6) shows the image information of recompile compression in the FPGA image data compression module (5).
2. a kind of method for compressing image based on wavelet transformation and clonal selection algorithm according to claim 1, it is characterized in that: the FPGA image data compression module (5) in the described step 4) comprises IMAQ coding module (11), sram cache module (7), wavelet transformation module (9), clonal selection algorithm module (8), display control module (10), and the compressed encoding processing method of described FPGA image data compression module (5) may further comprise the steps:
(a) described IMAQ coding module (11) gathers the image information in the SDRAM image buffer storage module (4) and it is buffered in the sram cache module (7);
(b) described wavelet transformation module (9) is carried out wavelet transformation to the image information that is stored in the sram cache module (7);
(c) described clonal selection algorithm module (8) is selected image information carry out Optimum wavelet base in the wavelet transformation in wavelet transformation module (9), and it is passed in wavelet transformation module (9) and the sram cache module (7);
(d) described display control module (10) obtains the view data of recompile compression in the sram cache module (7) and it is passed to image display (6).
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105704499A (en) * | 2016-01-25 | 2016-06-22 | 西北工业大学 | Selective satellite image compression encryption method based on Chacha20 and CCSDS |
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| US7181076B1 (en) * | 2000-07-26 | 2007-02-20 | Lockheed Martin Corporation | Wavelet-based data compression using principal components transformation |
| JP2007124619A (en) * | 2005-09-30 | 2007-05-17 | Ricoh Co Ltd | Image processor, image processing method, program, and information recording medium |
| CN101316364A (en) * | 2008-07-15 | 2008-12-03 | 南京信息工程大学 | Image compression system |
| CN101668204A (en) * | 2009-09-25 | 2010-03-10 | 西安电子科技大学 | Immune clone image compression method |
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| US7181076B1 (en) * | 2000-07-26 | 2007-02-20 | Lockheed Martin Corporation | Wavelet-based data compression using principal components transformation |
| JP2007124619A (en) * | 2005-09-30 | 2007-05-17 | Ricoh Co Ltd | Image processor, image processing method, program, and information recording medium |
| CN101316364A (en) * | 2008-07-15 | 2008-12-03 | 南京信息工程大学 | Image compression system |
| CN101668204A (en) * | 2009-09-25 | 2010-03-10 | 西安电子科技大学 | Immune clone image compression method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105704499A (en) * | 2016-01-25 | 2016-06-22 | 西北工业大学 | Selective satellite image compression encryption method based on Chacha20 and CCSDS |
| CN105704499B (en) * | 2016-01-25 | 2018-10-19 | 西北工业大学 | A kind of selective satellite image compression encryption method based on ChaCha20 and CCSDS |
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