CN110418141A - A kind of JPG format picture high-performance optimization method - Google Patents

A kind of JPG format picture high-performance optimization method Download PDF

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Publication number
CN110418141A
CN110418141A CN201910590419.XA CN201910590419A CN110418141A CN 110418141 A CN110418141 A CN 110418141A CN 201910590419 A CN201910590419 A CN 201910590419A CN 110418141 A CN110418141 A CN 110418141A
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quantization
picture
dct coefficient
jpg
jpg format
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王仁毅
肖文勇
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Hangzhou Mai Integrated Circuit Technology Co Ltd
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Hangzhou Mai Integrated Circuit Technology Co Ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102Methods 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
    • H04N19/124Quantisation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169Methods 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
    • H04N19/17Methods 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
    • H04N19/176Methods 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
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169Methods 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
    • H04N19/182Methods 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 a pixel
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169Methods 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
    • H04N19/186Methods 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 a colour or a chrominance component
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/48Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using compressed domain processing techniques other than decoding, e.g. modification of transform coefficients, variable length coding [VLC] data or run-length data
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/625Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using discrete cosine transform [DCT]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/90Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/91Entropy coding, e.g. variable length coding [VLC] or arithmetic coding

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Discrete Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

Disclosed by the invention is a kind of JPG format picture high-performance optimization method, comprising steps of reading original JPG format picture, takes out Huffman code table, quantifies table, the wide high and compressed macro block initial address of picture;Entropy decoding is carried out to macro block, the DCT coefficient after solving quantization;Inverse quantization is carried out to the DCT coefficient after quantization, restores practical DCT coefficient;The highest quantization table of compression ratio is selected, to practical DCT coefficient re-quantization;Entropy coding is carried out to the DCT coefficient after quantization;According to JPG file format, fill new quantization table, Huffman code table, new JPG format picture is generated, invention removes the complex calculations in conventional method, improve performance, reduce Memory Allocation, it can not disappear in Filled function picture and ruin data structure, the technical grades library such as middle libjpeg has more efficient process efficiency compared with the existing technology, and the optimization time of a picture reduces 80% than traditional technology.

Description

A kind of JPG format picture high-performance optimization method
Technical field
The present invention relates to a kind of picture high-performance optimization methods, more specifically say, are related to a kind of high property of JPG format picture Energy optimization method, belongs to picture process field.
Background technique
JPG is one of most popular picture format, is usually all deposited from the original JPG of the generations such as digital camera, mobile phone In the excessive problem of volume, in order to store and transmit, very more applications needs to carry out it equidimension and optimizes to reduce file Volume.Certain professional websites all specially have server to carry out media data optimization, under magnanimity traffic pressure, improve picture pressure Contract the performance optimized, has important practical significance.
JPG optimization is related to decoding and the coding techniques of bottom, directly relatively difficult from bottom layer realization.Existing optimization side Method is substantially realized using following 3 kinds of third party libraries: Libjpeg, ImagicMagick, FFmpeg.By these libraries, Thorough decompression is done to JPG picture first, generates original pixel data, then adjusts coding parameter, then is carried out primary complete JPG coding.
With problems and disadvantages existing for upper type:
1, image coding and decoding is a kind of work for consuming very much CPU, under massive concurrent, it is easy to cause CPU not enough, Number of concurrent is influenced, traffic handing capacity is reduced.
2, image coding and decoding is the biggish work of development difficulty, and more Internet company lacks the power of deep optimization.
3, time-consuming for image coding and decoding whole process, big for cpu load.
Summary of the invention
In order to solve above-mentioned prior art problem, the present invention provides to have and can reduce the optimization time, improve performance, reduce A kind of JPG format picture high-performance optimization method of the technical characterstics such as CPU requirement.
To achieve the goals above, the present invention is achieved by the following technical solutions:
A kind of JPG format picture high-performance optimization method, this method comprises the following steps:
Step 1): reading original JPG format picture, takes out Huffman code table, quantifies table, and picture is wide high and compressed Macro block initial address;
Step 2): entropy decoding is carried out to macro block, the DCT coefficient after solving quantization;
Step 3): inverse quantization is carried out to the DCT coefficient after quantization, restores practical DCT coefficient;
Step 4): the 30 grades of quantization tables defined using open source software FFMPEG select 20 grades or more of high compression rate quantization Table, to practical DCT coefficient re-quantization, wherein the 1st grade be picture quality highest, compression ratio it is minimum, the 30th grade is picture quality Minimum, compression ratio highest;
Step 5): entropy coding is carried out to the DCT coefficient after quantization in step 4) using new Huffman table, is compiled again Data after code;
Step 6): according to JPG file format, 20 grades or more in step 4) of high compression rate is quantified into table, in step 5) Huffman code table and the data write-in JPG file after recompiling, generate new JPG format picture.
As an improvement step 2) medium entropy decoding process are as follows:
A) macro block is divided into several data cells DU by brightness and color first, the data in each data cell DU are again It is divided into two classes, one kind is the DC data crossed with differential encoding, and another kind of is the exchange data crossed with Run- Length Coding;
B) two kinds of data are first unified to carry out a normal form Hafman decoding, then carries out DPCM and RLE solution respectively again Code, last solution go out the DCT coefficient after quantifying.
As an improvement de-quantization process:
A) the quantization table obtained in step 1) multiplying realization is carried out with the DCT coefficient obtained in step 2) to restore DCT coefficient.
As an improvement the differential encoding uses DPCM, the Run- Length Coding uses RLE.
As an improvement Huffman table new in step 5) comes from open source software FFMPEG, using normal form Huffman lattice Formula definition.
As an improvement every 16x16 pixel is divided into a macro block on JPG format picture.
The utility model has the advantages that eliminating DCT, IDCT, YUV, RGB operation in conventional method, performance is greatly improved, reduces Memory Allocation, can not disappear in Filled function picture and ruin data structure, can share Huffman table;Entire optimization can incite somebody to action The optimization performance of JPG accomplishes that most preferably the technical grades library such as middle libjpeg has more efficient process efficiency compared with the existing technology; It can optimize from bottom layer realization JPG format picture, increase substantially the optimization performance of JPG format picture, the optimization of a picture Time reduces 80% than traditional technology.
Detailed description of the invention
Fig. 1 is the optimized flow chart of traditional JPG format picture.
Fig. 2 is the optimized flow chart of JPG format picture of the present invention.
Fig. 3 is 30 grades of quantization tables that FFMPEG is defined in the present invention.
Fig. 4 is the Huffman code table that FFMPEG is defined in the present invention.
Specific embodiment
Below in conjunction with Figure of description, the invention will be further described, but the invention is not limited to following embodiments.
It is as shown in Figure 1 the optimized flow chart of tradition JPG format picture, specific: JPG format picture decoding process can divide For 5 steps:
1, resolution file format takes out Huffman code table, quantifies table, the wide height of picture, compressed macro block initial address.
2, decoded macroblock, first macro block are divided into several DU by brightness and color, and the data in each DU are divided into two classes again, One kind is the DC data crossed with differential encoding, and one kind is the exchange data crossed with Run- Length Coding, both data, first unify into Then normal form Hafman decoding of row distinguishes DPCM and RLE decoding, the data finally solved again.
3, inverse quantization carries out multiplying, reduction with the data solved in step 2 by the quantization table taken out in step 1 DCT coefficient out.
4, IDCT (discrete cosine transform inverse transformation) inputs 64 data, 64 data is exported, eventually by step 3 DCT coefficient calculate actual pixel data, which is yuv format, and step 4) logic is simple, but operand is huge Greatly, disadvantage is obvious.
5, YUV turns RGB, generally also needs yuv data to change into RGB to show, RGB may be considered the original of picture Data, what is actually solved here is the region of a 16x16 size, repeats process above, so that it may decode whole figure Piece.
The cataloged procedure of JPG: JPG format picture decoding process reverse operating, that is, JPG cataloged procedure.
Above-mentioned DCT/IDCT is analogous to a kind of mathematical method of Fourier transform, belongs to the core of JPG encoding and decoding, JPG Format picture decoding, coding step 3 are the key that JPG optimization, by different quantization tables, the number of significant digit of coefficient can be allowed to send out Changing finally causes the variation of the quality and volume of picture.
It is found by the prior art, in order to optimize JPG format picture, is once decoded, then carry out first encoding again, Essence is and the re-quantization just for the sake of re-quantization, it is only necessary to which the data got in step 3 can be realized, subsequent step Suddenly it is redundancy, for example carries out IDCT when decoding, when coding, carries out DCT, this is an inverse operation, after a positive and a negative converts twice, Data are returned to initial value, and any variation will not occur, be also equal to the data taken out in step 3, it is clear that should remove this A little operations.
It is illustrated in figure 2 the optimized flow chart of JPG format picture of the present invention, specific embodiment 1:
A kind of JPG format picture high-performance optimization method, this method comprises the following steps:
Step 1): reading original JPG format picture, takes out Huffman code table, quantifies table, and picture is wide high and compressed Macro block initial address, every 16x16 pixel is divided into a macro block on general JPG format picture;
Step 2): entropy decoding is carried out to macro block, the DCT coefficient after solving quantization;
Entropy decoding process are as follows:
A) macro block is divided into several data cells DU by brightness and color first, the data in each data cell DU are again It is divided into two classes, one kind is the DC data crossed with differential encoding, and another kind of is the exchange data crossed with Run- Length Coding, differential encoding Using DPCM, the Run- Length Coding uses RLE;
B) two kinds of data are first unified to carry out a normal form Hafman decoding, then carries out DPCM and RLE solution respectively again Code, last solution go out the DCT coefficient after quantifying;
Step 3): inverse quantization is carried out to the DCT coefficient after quantization, restores practical DCT coefficient;De-quantization process:
A) the quantization table obtained in step 1) multiplying realization is carried out with the DCT coefficient obtained in step 2) to restore DCT coefficient;
Step 4): the 30 grades of quantization tables defined using open source software FFMPEG select 20 grades or more of high compression rate quantization Table, to practical DCT coefficient re-quantization, wherein the 1st grade is minimum for picture quality highest compression ratio, the 30th grade for picture quality most Little compressible highest, human eye are so sensitive to the susceptibility of the high-frequency signal low frequency signal that is far from, so cannot be using simple Equal proportion quantization, quantization step should be that high frequency is long, the short non-linear relation of low frequency, to need to define 64 numerical value Quantify table, quantization table is one group of constant value, is the empirical data obtained from extensive experiment, in the present solution, using industry The 30 grades of quantization tables (referring to fig. 4) defined in the widely used open source software FFMPEG in boundary, wherein the 1st grade of picture quality highest Compression ratio is minimum, the 30th grade of picture quality minimal pressure shrinkage highest;
Step 5): entropy coding is carried out to the DCT coefficient after quantization in step 4) using new Huffman table, is compiled again Data after code, new Huffman table are as follows: can be (except original different from the Huffman code table taken out in original JPG format picture Huffman code table in JPG format picture), it is preferable to use one group of new Huffman code tables (referring to figure in the process for entropy coding 4) open source software FFMPEG, is come from, it is the empirical data obtained from extensive experiment that Huffman table, which is one group of constant value, Statistically, it can guarantee that Huffman encoding can have high compression rate;
Step 6): according to JPG file format, 20 grades or more in step 4) of high compression rate is quantified into table, in step 5) Huffman code table and the data write-in JPG file after recompiling, generate new JPG format picture.
In conjunction with Fig. 2 it is found that when JPG format picture optimizes, decoding only needs to solve to step 3 (half decodes), then directly uses New quantization table re-quantization, starting encodes immediately later, it is only necessary to carry out entropy coding again (half encodes), so that it may be formed new JPG format picture file.
Embodiment 2 does contrast test with the CPU of 2.20GHz, and the picture of test is the lena_ that resolution ratio is 512*512 std.jpg。
Detailed process:
Step 1): reading file lena_std.jpg, takes out Huffman code table, quantifies table, after picture is wide high and compression Macro block initial address, image file size 224K, a height of 512x512 of image width;
Step 2): entropy decoding is carried out to macro block, the DCT coefficient after solving quantization;
Step 3): inverse quantization is carried out to the DCT coefficient after quantization, restores practical DCT coefficient;
Step 4): selecting the quantization table of high compression rate, to the direct re-quantization of practical DCT coefficient, the quantization selected herein Table be 8,44,44,52,44,52,60,60,60,60,60,60,71,66,71,74,74,74,71,71,71,71,74,74, 74,79,79,79,93,93,93,79,79,79,74,74,79,79,88,88,93, 93,101,104,101,96,96,93, 96,104,104,110,110,110,132,132,126,126,154, 154,159,189,189,228};
Step 5): entropy coding is carried out to the DCT coefficient after quantization;
Step 6): according to JPG file format, new quantization table is filled, Huffman code table generates new JPG picture, most The picture size obtained eventually is 10K, 7 milliseconds (CPU 2.20GHz, Ubuntu16.04) of time-consuming.
Optimum results and traditional technology optimum results contrast test table in embodiment 2:
Prioritization scheme Runing time
FFmpeg 85ms
ImagicMagick 59ms
Libjpeg 40ms
The present invention 7ms
As can be seen that actual effect of the present invention uses the time than the CPU that traditional technology reduces 80% or more.
Finally it should be noted that present invention is not limited to the above embodiments, there can also be many variations.This field it is general All deformations that logical technical staff directly can export or associate from present disclosure, are considered as of the invention Protection scope.

Claims (6)

1. a kind of JPG format picture high-performance optimization method, it is characterised in that this method comprises the following steps:
Step 1): reading original JPG format picture, takes out Huffman code table, quantifies table, the wide high and compressed macro block of picture Initial address;
Step 2): entropy decoding is carried out to macro block, the DCT coefficient after solving quantization;
Step 3): inverse quantization is carried out to the DCT coefficient after quantization, restores practical DCT coefficient;
Step 4): the 30 grades of quantization tables defined using open source software FFMPEG select 20 grades or more of high compression rate to quantify table, right Practical DCT coefficient re-quantization, wherein the 1st grade minimum for picture quality highest, compression ratio, the 30th grade it is minimum for picture quality, Compression ratio highest;
Step 5): entropy coding is carried out to the DCT coefficient after quantization in step 4) using new Huffman table, after being recompiled Data;
Step 6): according to JPG file format, 20 grades or more in step 4) of high compression rate is quantified into table, the Hough in step 5) Graceful code table and the data write-in JPG file after recompiling, generate new JPG format picture.
2. a kind of JPG format picture high-performance optimization method according to claim 1, it is characterised in that: step 2) medium entropy Decoding process are as follows:
A) macro block is divided into several data cells DU by brightness and color first, the data in each data cell DU are divided into again Two classes, one kind are the DC datas crossed with differential encoding, and another kind of is the exchange data crossed with Run- Length Coding;
B) two kinds of data are first unified to carry out a normal form Hafman decoding, then carries out DPCM and RLE decoding respectively again, finally DCT coefficient after solving quantization.
3. a kind of JPG format picture high-performance optimization method according to claim 1 or 2, it is characterised in that: inverse quantization mistake Journey:
A) DCT coefficient obtained in the quantization table obtained in step 1) and step 2) is subjected to multiplying realization and restores DCT Coefficient.
4. a kind of JPG format picture high-performance optimization method according to claim 2, it is characterised in that: the difference is compiled Code uses DPCM, and the Run- Length Coding uses RLE.
5. a kind of JPG format picture high-performance optimization method according to claim 1 or 2 or 4, it is characterised in that: JPG lattice Every 16x16 pixel is divided into a macro block on formula picture.
6. a kind of JPG format picture high-performance optimization method according to claim 1 or 2, it is characterised in that: in step 5) New Huffman table comes from open source software FFMPEG, is defined using normal form Huffman format.
CN201910590419.XA 2019-07-02 2019-07-02 A kind of JPG format picture high-performance optimization method Pending CN110418141A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112911289A (en) * 2021-05-10 2021-06-04 杭州雄迈集成电路技术股份有限公司 DCT/IDCT transformation optimization method and system

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1339922A (en) * 2000-08-18 2002-03-13 株式会社媒体糊 Separating and merging device, method for coding signal and computer program product

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1339922A (en) * 2000-08-18 2002-03-13 株式会社媒体糊 Separating and merging device, method for coding signal and computer program product

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112911289A (en) * 2021-05-10 2021-06-04 杭州雄迈集成电路技术股份有限公司 DCT/IDCT transformation optimization method and system

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Application publication date: 20191105