CN109493345A - A kind of quick Processing Algorithm of computer digital image - Google Patents
A kind of quick Processing Algorithm of computer digital image Download PDFInfo
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- CN109493345A CN109493345A CN201811282065.4A CN201811282065A CN109493345A CN 109493345 A CN109493345 A CN 109493345A CN 201811282065 A CN201811282065 A CN 201811282065A CN 109493345 A CN109493345 A CN 109493345A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding
Abstract
The invention discloses a kind of quick Processing Algorithms of computer digital image, include the following steps: step 1, image segmentation；Step 2 extracts IFS code；Step 3, it is conventional to encode；Step 4, coefficient matrix calculate；Step 5, transformation of coefficient；Step 6, reconstructed image；Wherein in above-mentioned step one, choose the processing platform that suitable operating system is handled as computer digital image, transformation is implemented using transformation base for original image, obtain four subgraphs of image: LL, LH, HL, HH, and LL subgraph is divided into the domain blocks of 2m*2n size, it is described using set D, image is divided into the range block that size is m*n, is described using set R；The present invention, it is possible to reduce the time spent by Digital Image Processing, can be effectively reduced the blocking artifact of Digital Image Processing generation, boosting algorithm encoded SNR (Signal to Noise Ratio) effectively improves the quality of image procossing, improves the validity and accuracy of algorithm.
Description
Technical field
The present invention relates to field of computer technology, specially a kind of quick Processing Algorithm of computer digital image.
Background technique
Digital Image Processing (Digital Image Processing) is also known as Computer Image Processing, is to pass through calculating
Machine is removed noise, enhancing, recovery, segmentation, the methods and techniques for extracting the processing such as feature to image；It is usually necessary to use spies
Fixed algorithm carries out image procossing, Digital Image Processing algorithm in the prior art, and processing speed is slower, it usually needs expends
The a large amount of time, meanwhile, Digital Image Processing algorithm in the prior art, in the matter that can reduce image after algorithm process
Amount, influences the quality of image, and therefore, it is necessary for designing a kind of quick Processing Algorithm of computer digital image.
Summary of the invention
The purpose of the present invention is to provide a kind of quick Processing Algorithms of computer digital image, to solve above-mentioned background technique
The problem of middle proposition.
To achieve the above object, the invention provides the following technical scheme:
A kind of quick Processing Algorithm of computer digital image, includes the following steps: step 1, image segmentation；Step 2 mentions
Take IFS code；Step 3, it is conventional to encode；Step 4, coefficient matrix calculate；Step 5, transformation of coefficient；Step 6, reconstruct image
Picture；
Wherein in above-mentioned step one, it is flat to choose the processing that suitable operating system is handled as computer digital image
Platform implements transformation using transformation base for original image, obtains four subgraphs of image: LL, LH, HL, HH, and LL subgraph is drawn
It is divided into the domain blocks of 2m*2n size, is described using set D, image is divided into the range block that size is m*n, is used
Set R is described；
Wherein in above-mentioned step two, by each of domain set D DjStretched, it is affine and translation etc. eight
The relevant transformation W of kindj, wherein j=1,2,3 ... 8, after pattern conversion, to domain blocks Wj(Dj) associated range block Ri
Formula 1:D can be used in relevant mappings=s (Wj(Dj))+ol, calculate the range block R that defines domain mapping and will encodeiIt
Between existing error amount, calculating process such as formula 2:And find RiThe smallest definition of error
Domain block, is set to best matching blocks, records the position of this domain blocks, and the value of s and o is calculated with formula 1 out:
Wherein in above-mentioned step three, after the value by calculating s and o in step 2, conventional volume is carried out to IFS code
Code；
It wherein in above-mentioned step four, repeats the above steps, all units in strong range block R is all compiled
Code, and using coding parameter obtained in step 3 and correlating transforms coefficient x=Ψ Θ, y=the Φ Ψ Θ of Ψ, to coding
Image is decoded F, using Fourier transformation F1 ← (LL-F) obtain difference subgraph F1, available coefficient matrix,
Wherein in above-mentioned step five, transformation of coefficient is carried out to matrix B, and measured value is obtained by Ψ, and pass through survey
Magnitude decodes F ' with OMP algorithm；
Wherein in above-mentioned step six, matrix F is merged with F, then anti-wavelet transformation, obtains reconstructed image.
According to the above technical scheme, in the step 1, the operating platform of selection is Matlab2015 integrated platform.
According to the above technical scheme, in the step 1, using Dabechies9/7 as transformation base.
According to the above technical scheme, in the step 2, s is contrast factor, and o is the intensity deviation factor, and l is unit square
Battle array.
According to the above technical scheme, in the step 4, Θ is the rarefaction representation of signal X, and Ψ is the calculation matrix of M*N.
Compared with prior art, the beneficial effects of the present invention are: it is of the invention, Matlab2015 integrated platform is chosen, is convenient for
Operational data, is conducive to the accuracy and validity that show algorithm, and the display effect by the image after algorithm process is more clear
It is clear, the time spent by Digital Image Processing is also greatly reduced, the blocking artifact of Digital Image Processing generation is effectively reduced, is promoted
Algorithm coding signal-to-noise ratio effectively improves the quality of image procossing, improves the validity and accuracy of algorithm.
Detailed description of the invention
Fig. 1 is algorithm flow chart of the invention；
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to Fig. 1, the present invention provides a kind of technical solution:
A kind of quick Processing Algorithm of computer digital image, includes the following steps: step 1, image segmentation；Step 2 mentions
Take IFS code；Step 3, it is conventional to encode；Step 4, coefficient matrix calculate；Step 5, transformation of coefficient；Step 6, reconstruct image
Picture；
Wherein in above-mentioned step one, it is flat to choose the processing that suitable operating system is handled as computer digital image
Platform implements transformation using transformation base for original image, obtains four subgraphs of image: LL, LH, HL, HH, and LL subgraph is drawn
It is divided into the domain blocks of 2m*2n size, is described using set D, image is divided into the range block that size is m*n, is used
Set R is described；
Wherein in above-mentioned step two, by each of domain set D DjStretched, it is affine and translation etc. eight
The relevant transformation W of kindj, wherein j=1,2,3 ... 8, after pattern conversion, to domain blocks Wj(Dj) associated range block Ri
Formula 1:D can be used in relevant mappings=s (Wj(Dj))+ol, calculate the range block R that defines domain mapping and will encodeiIt
Between existing error amount, calculating process such as formula 2:And find RiThe smallest definition of error
Domain block, is set to best matching blocks, records the position of this domain blocks, and the value of s and o is calculated with formula 1 out:
Wherein in above-mentioned step three, after the value by calculating s and o in step 2, conventional volume is carried out to IFS code
Code；
It wherein in above-mentioned step four, repeats the above steps, all units in strong range block R is all compiled
Code, and using coding parameter obtained in step 3 and correlating transforms coefficient x=Ψ Θ, y=the Φ Ψ Θ of Ψ, to coding
Image is decoded F, using Fourier transformation F1 ← (LL-F) obtain difference subgraph F1, available coefficient matrix,
Wherein in above-mentioned step five, transformation of coefficient is carried out to matrix B, and measured value is obtained by Ψ, and pass through survey
Magnitude decodes F ' with OMP algorithm；
Wherein in above-mentioned step six, matrix F is merged with F, then anti-wavelet transformation, obtains reconstructed image.
According to the above technical scheme, in step 1, the operating platform of selection is Matlab2015 integrated platform, is convenient for operation
Data are conducive to the accuracy and validity that show algorithm.
According to the above technical scheme, in step 1, using Dabechies9/7 as transformation base, convenient for the related letter of description
Number, be conducive to improve accuracy when reconstructed image.
According to the above technical scheme, in step 2, s is contrast factor, and o is the intensity deviation factor, and l is unit matrix.
According to the above technical scheme, in step 4, Θ is the rarefaction representation of signal X, and Ψ is the calculation matrix of M*N.
Based on above-mentioned, it is an advantage of the current invention that it is of the invention, suitable operating system is chosen as computer digital image
The processing platform of processing, the operating platform of selection are Matlab2015 integrated platform, are convenient for operational data, are conducive to show algorithm
Accuracy and validity, for original image using transformation base implement transformation, using Dabechies9/7 as transformation base, just
In description coherent signal, is conducive to improve accuracy when reconstructed image, obtains four subgraphs of image: LL, LH, HL, HH, and
LL subgraph is divided into the domain blocks of 2m*2n size, is described using set D, image is divided into the value that size is m*n
Domain block is described using set R；By each of domain set D DjStretched, it is affine to translation etc. eight kinds it is related
Transformation Wj, wherein j=1,2,3 ... 8, after pattern conversion, to domain blocks Wj(Dj) associated range block RiIt is relevant
Formula 1:D can be used in mappings=s (Wj(Dj))+ol, calculate the range block R that defines domain mapping and will encodeiBetween exist
Error amount, calculating process such as formula 2:And find RiThe smallest domain blocks of error,
Best matching blocks are set to, the position of this domain blocks is recorded, and the value of s and o is calculated with formula 1 out, s is comparison
The factor is spent, o is the intensity deviation factor, and l is unit matrix: after the value for calculating s and o, conventional coding being carried out to IFS code；Weight
Multiple above-mentioned steps, all encode all units in strong range block R, and utilize obtained coding parameter and Ψ
Correlating transforms coefficient x=Ψ Θ, y=Φ Ψ Θ, is decoded F to coded image, is obtained using Fourier transformation F1 ← (LL-F)
Difference subgraph F1, available coefficient matrix,Θ is the rarefaction representation of signal X, and Ψ is M*N's
Calculation matrix；Transformation of coefficient is carried out to matrix B, and measured value is obtained by Ψ, and F ' is decoded by measured value OMP algorithm；
Matrix F is merged with F, then anti-wavelet transformation, obtains reconstructed image；The present invention, it is possible to reduce when spent by Digital Image Processing
Between, it can be effectively reduced the blocking artifact of Digital Image Processing generation, boosting algorithm encoded SNR (Signal to Noise Ratio) effectively improves image procossing
Quality, improve the validity and accuracy of algorithm.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to
Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (5)
1. a kind of quick Processing Algorithm of computer digital image, includes the following steps: step 1, image segmentation；Step 2 is extracted
IFS code；Step 3, it is conventional to encode；Step 4, coefficient matrix calculate；Step 5, transformation of coefficient；Step 6, reconstructed image；
It is characterized by:
Wherein in above-mentioned step one, the processing platform that suitable operating system is handled as computer digital image is chosen,
Transformation is implemented using transformation base for original image, obtains four subgraphs of image: LL, LH, HL, HH, and LL subgraph is divided
It for the domain blocks of 2m*2n size, is described using set D, image is divided into the range block that size is m*n, uses collection
R is closed to be described；
Wherein in above-mentioned step two, by each of domain set D DjStretched, it is affine and translation etc. eight kinds of phases
The transformation W of passj, wherein j=1,2,3 ... 8, after pattern conversion, to domain blocks Wj(Dj) associated range block RiIt is related
Mapping formula 1:D can be useds=s (Wj(Dj))+ol, calculate the range block R that defines domain mapping and will encodeiBetween deposit
Error amount, calculating process such as formula 2:And find RiThe smallest domain of error
Block is set to best matching blocks, records the position of this domain blocks, and the value of s and o is calculated with formula 1 out:
Wherein in above-mentioned step three, after the value by calculating s and o in step 2, conventional coding is carried out to IFS code；
It wherein in above-mentioned step four, repeats the above steps, all units in strong range block R is all encoded, and
Using coding parameter obtained in step 3 and correlating transforms coefficient x=Ψ Θ, y=the Φ Ψ Θ of Ψ, to coded image into
Row decoding F, using Fourier transformation F1 ← (LL-F) obtain difference subgraph F1, available coefficient matrix,
Wherein in above-mentioned step five, transformation of coefficient is carried out to matrix B, and measured value is obtained by Ψ, and pass through measured value
F ' is decoded with OMP algorithm；
Wherein in above-mentioned step six, matrix F is merged with F, then anti-wavelet transformation, obtains reconstructed image.
2. the quick Processing Algorithm of a kind of computer digital image according to claim 1, it is characterised in that: the step 1
In, the operating platform of selection is Matlab2015 integrated platform.
3. the quick Processing Algorithm of a kind of computer digital image according to claim 1, it is characterised in that: the step 1
In, using Dabechies9/7 as transformation base.
4. the quick Processing Algorithm of a kind of computer digital image according to claim 1, it is characterised in that: the step 2
In, s is contrast factor, and o is the intensity deviation factor, and l is unit matrix.
5. the quick Processing Algorithm of a kind of computer digital image according to claim 1, it is characterised in that: the step 4
In, Θ is the rarefaction representation of signal X, and Ψ is the calculation matrix of M*N.
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Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106612439A (en) * | 2016-02-04 | 2017-05-03 | 四川用联信息技术有限公司 | Adaptive fast fractal image compression method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106612439A (en) * | 2016-02-04 | 2017-05-03 | 四川用联信息技术有限公司 | Adaptive fast fractal image compression method |
Non-Patent Citations (1)
| Title |
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| 彭利华 等: "一种基于压缩感知图像编码算法研究", 《南华大学学报(自然科学版)》 * |
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Application publication date: 20190319 |