CN1460969A - Hierarchy tree set partition image coding decoding method based of digital signal processor - Google Patents
Hierarchy tree set partition image coding decoding method based of digital signal processor Download PDFInfo
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Abstract
The present invention relates to a SPIHT image coding/decoding method based on digital singnal processor. When coding, the treatment object is the transformation coefficient after wavelet transformation, firstly, initializing SPIHT image coded data structure, then according to the current plane threshold making comparison judging that the place coefficient is important or not at current position, sequentially scanning tate table and making the wavelet transformation coefficient undergo the process of bit-plane thinning treatment, splicing outputted bit information and forming final code flow; and when decoding, the treatment object is the wavelet transformation coefficient after the SPIHT is coded, firstly, initializing SPIHT image decoded data structure, inputting information from code flow according to bit, then sequentially scanning state table and making SPIHT decoding process according to input information.
Description
Technical field
The present invention relates to a kind of image coding/decoding method, particularly a kind of hierarchical tree set partitioned image decoding method based on digital signal processor.
Background technology
At present, wavelet transformation is as the international standard of JPEG2000, is widely used in fields such as the static texture information compression of JEPG2000, MPEG4 and Medical Image Compression.But,, also be among the continuous development at present because the efficient of the code decode algorithm of coefficient behind the wavelet transformation is directly influenced coding and decoding video efficient based on wavelet transformation.And the compression of wavelet coefficient is normally carried out at whole two field picture, it is very harsh to the processing speed and the memory requirement of hardware in hardware is realized, brought difficulty for the real-time implementation of hardware, so wavelet transformation uses lessly in product, particularly hardware realization aspect still less.
Image is behind wavelet transformation, and its coefficient mainly contains two characteristics:
First characteristics are concentration of energy: most of concentration of energy of image is at low frequency sub-band, energy among all the other frequency bands mainly concentrates on the sub-band coefficients place corresponding with the jump in brightness edge of image, and the absolute value of the low layer coefficients of the high-rise coefficient ratio of general homology is big.
Second characteristic is self similarities: between the different layers of same class subband, have the characteristics of self-similarity usually.The self similarity of this interlayer on the one hand, is reflected in similar corresponding between the position of the big coefficient of each layer at edge; On the other hand, also be reflected on the interlayer relation of little coefficient, generally also smaller with the coefficient of a corresponding low layer of little coefficient.
Back one characteristics have derived the notion of zero tree.Shapiro forms the structure of setting to wavelet coefficient, defines certain stalk tree for zero tree under the current threshold value, if all coefficients that this stalk is set are all little than this threshold value.
(Set Partitioning in HierarchicalTrees SPIHT) has inherited the thought of zero-tree wavelet coding techniques to the coding method of hierarchical tree set divided image, utilizes between the different scale self-similarity between the image wavelet transform coefficient to encode.Wavelet coefficient is important in non-important about a given threshold value, depends on whether this wavelet coefficient surpasses this threshold value.Image wavelet transform coefficient and one group of threshold value of successively decreasing compare, thereby wavelet conversion coefficient is made into a kind of order subset by coefficient amplitude size groups.
One of principal character of SPIHT coding method is that sorting data does not directly transmit, and is based on such fact: the execution path of algorithm is by the comparative result definition of branch node.So if Code And Decode has same sort algorithm, decoding just can utilize and the identical execution path of encoding so.If demoder can obtain coefficient amplitude comparative result, sequencing information just can recover from same execution path.
Existing SPIHT coding method utilizes list structure to realize data structure, when yet list structure is realized for hardware, because the restriction of addressing mode, can increase unnecessary computational complexity and time overhead, the operational efficiency of algorithm is reduced greatly, advantage owing to list structure is an elongated structure again, but for the hardware that fixed resource is arranged, the meaning of elongated structure is also not obvious.
In addition, existing SPIHT coding method scans by the frequency band bitplanes, but, press the frequency scan order, as shown in Figure 1, basically, be a kind of structure of tree-like scanning, the advantage of this Scan Architecture is at the self-similarity that has made full use of on the order of output code flow between each frequency band.But the same with list structure, this irregular scan mode makes data addressing become complicated.And because the memory headroom of DSP is limited, and the data volume of a two field picture is very big, can not all be stored in sheet stored district, a part of data can only be put in the sheet, to increase the travelling speed of algorithm.The characteristics of handling LIS in the spiht algorithm have determined that the correlativity between each frequency band data is very big, if adopt tree-like scanning, as shown in Figure 2, adopt and press frequency scan, if the ranks scope of this frequency band is (m1, n1)～(m2, n2), then directly related with this frequency band data address scope is (2 * m1,2 * n1)～(1+2 * m2,1+2 * n2), jumping in storage in the address of related data, can't call in internal memory simply continuously.
This shows that present SPIHT code decode algorithm structure lacks uses specific aim, is not easy to the hardware realization.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of SPIHT image coding/decoding method based on digital signal processor, makes the addressing of data more regular, improves the encoding and decoding operational efficiency, is beneficial to hardware and realizes.
The invention provides a kind of SPIHT method for encoding images, at first carry out the data structure initialization of SPIHT picture coding based on digital signal processor; Compare according to threshold value then, judge whether important at the present bit floor coefficient when frontal plane; The sequential scanning state table carries out the bit plane refinement to wavelet coefficient; The bit information of output is spliced and forms final code stream.
Accordingly, the present invention also provides a kind of SPIHT picture decoding method based on digital signal processor, at first carry out the data structure initialization of SPIHT picture coding, from code stream, press the bit input information, the sequential scanning state table carries out the bit plane refinement of SPIHT coding according to input information then.
SPIHT image coding/decoding method based on digital signal processor provided by the invention, because using fixedly, two-dimensional array has replaced original list structure, use sequential scanning to replace by frequency scan, make the addressing of data more regular, data data throughput between interior external memory is easier, thereby makes that the hardware efficient when realizing with buffering is higher.
Description of drawings
Fig. 1 is the synoptic diagram that SPIHT coding of the prior art scans by the frequency band bitplanes;
Fig. 2 is the data addressing synoptic diagram of SPIHT coding of the prior art by frequency scan;
Fig. 3 is the SPIHT method for encoding images process flow diagram that the present invention is based on digital signal processor;
Fig. 4 is the LIST two-dimensional array synoptic diagram that the present invention uses;
Fig. 5 is the SDL two-dimensional array synoptic diagram that the present invention uses;
Fig. 6 is the data addressing synoptic diagram by the row sequential scan mode that the present invention uses;
Fig. 7 is an initialization procedure of the present invention.
Fig. 8 is the SPIHT picture decoding method process flow diagram that the present invention is based on digital signal processor.
Embodiment
The invention provides a kind of SPIHT method for encoding images based on digital signal processor, as shown in Figure 3, during coding, process object is the conversion coefficient behind the wavelet transformation, at first to the data structure initialization (step 301) of SPIHT picture coding; Then according to comparing, judge in present bit floor coefficient whether important (step 302) when the threshold value of frontal plane; The sequential scanning state table carries out bit plane refinement (step 303) to wavelet coefficient; The bit information of output is spliced and forms final code stream (step 304).
Continue coding if desired, then number of bit-planes is subtracted 1, return step (2).
Wherein, the described data structure of step 301 is to have replaced original list structure with two-dimensional array, therefore, we can be referred to as not have the set of chained list hierarchical tree and divide (Non-List Set Partitioning inHierarchical Trees, NL SPIHT), initialization to this two-dimensional array comprises: the symbol of wavelet coefficient is separated with absolute value, calculate the maximum value bit plane of wavelet coefficient; Calculate maximum descendants's value of all coefficients that the offspring is arranged; The array of non-important pixel LIP, important pixel LSP and three states of non-important set LIS is represented in initialization, with a unified two-dimensional array state table LIST representative.
As shown in Figure 4, the LIST two-dimensional array is represented the state of adjacent two coefficients in the former matrix of coefficients with a byte, and size is 1/2 of a former matrix of coefficients, and LIS represents that with two bits LIP and LSP represent with two bits, and LSP is empty when initialization.Wherein A1A2B1B2 represents the state of i data, and C1C2D1D2 represents the state of i+1 data:
A1A2: expression LIS state B1B2: expression LIP, LSP state
01-----a class LIS 01----LIP
10-----b class LIS 10----LSP
00-----ignores 00----and ignores
As shown in Figure 5, a byte is represented the state that offspring's coefficient is arranged in the former matrix of coefficients in the SDL two-dimensional array, the most significant digit plane value of storage SD and SL, and wherein SD represents to comprise all offsprings of direct offspring, SL represents not comprise direct offspring's indirect offspring.1 byte can be represented the SD and the SL most significant digit plane value value of a LIS coefficient, wherein high four bit representation SLmax bit plane values, low four bit representation SDmax bit plane values.
In the two-dimensional array SDL of maximum descendants's value of preserving all coefficients that the offspring is arranged, a byte can be represented maximum descendants's value of two adjacent coefficients, the specific implementation method can be used binary form, uses four bits that peaked most significant digit plane is replaced numerical value itself.For example: maximum descendants's value of adjacent two coefficients is respectively max1=1000, max2=500,2
9＜max1＜2
10, 2
8＜max2＜2
9, therefore, dominant bit plane=9 (0x1001) of max1, dominant bit plane=8 (0x1000) of max2 are represented with 0x10001001 in SDL.Begin coding from the most significant digit plane.
If a two field picture is carried out 4 layers of wavelet transformation, concrete initialization of the present invention as shown in Figure 7.
Coefficient in the step 302 is the sequential scan mode that adopts by row, if number of bit-planes is N, judge whether important at the present bit floor coefficient, employing threshold value 2
NCompare,, comprise among capable and the 2nd * n+1 row coefficient of the 2nd * n of all direct offsprings of this row coefficient and corresponding state table LIST, the SDL thereof the place line number and put into internal memory, to improve counting yield with the current line coefficient n of prescan.
The scanning sequency of coefficient array is consistent with the change of state array in proper order, and therefore, sequential scanning is two-dimensional state array LIST service in the present invention.Two-dimensional array replaces the advantage of chained list to be that addressing mode is simple, direct, and this advantage has been strengthened in sequential scanning more, make addressing mode simpler, as shown in Figure 6, the related data that the coding of one row coefficient relates to is lacked a lot than the related data of a frequency band, if when the line data of pre-treatment is that m is capable, then only the 2nd * m and the 2nd * m+1 line data need be called in internal memory and get final product.
The sequential scanning state table in state table, is labeled as the coefficient of important pixel LSP on the present bit plane, will become the some refinement output of important pixel on the present bit plane, exports the corresponding bit information of coefficient in control bit information and the coefficient table simultaneously;
The sequential scanning state table, in state table, be labeled as the coefficient of non-important pixel LIP on the present bit plane, scan on the present bit plane, according to the comparison of present bit plane threshold value, again change the bit of LSP and LIP in the state table, be re-assigned to LSP or LIP, export the corresponding bit information of coefficient in control bit information and the coefficient table simultaneously;
The sequential scanning state table, in state table, be labeled as the coefficient of non-important pixel collection LIS on the present bit plane, will be according to the algorithm of zero tree division, inquire about corresponding SDL with it in showing information and direct offspring's coefficient magnitude, by with the comparison of present bit plane threshold value, judge and be split into non-important set, non-important pixel and important pixel again, revise the corresponding bits position in the LIST state table, export the corresponding bit information of coefficient in control bit information and the coefficient table simultaneously.
The described final code stream output of step 304, can use the way of output of single-bit, but consider that frequent individual bit output reduces the operational efficiency of algorithm, so the present invention also can separate the bit output of SPIHT with the code stream splicing, bit output to SPIHT saves as variable length code earlier, splice these variable length codes by special function then, for example, can be in 32 vbr buffer districts of an integer (int) with the first centralized stores of some bits, according to the round-robin implementation status, with function the variable length code in the buffer zone is spliced to output code flow again after reaching certain number, can improves the travelling speed of algorithm like this.
The processing sequence of spiht algorithm is that the bit plane according to data carries out, calling of data is very frequent, and because whole frame image data amount is very big, can not leave the sheet stored district of DSP in, and need leave in outside the sheet, calling repeatedly of data reduces the algorithm operational efficiency.Because the present invention is based on the algorithm of DSP and realizes, makes full use of the characteristics of DSP, can improve the operational efficiency of algorithm.For example, in the series DSP of TIC6x, DMA (direct memory visit) can be between the zones of different of storage space transferring data, this access visit need not the intervention of CPU, finishes all control by dma controller.Dma controller is independent of CPU work, has monocyclic data throughput, have address producing method and multiple transmission data word length flexibly, in the realization of algorithm, can be when handling data line, finish the carrying of lastrow or next line data, most data carrying and transform operation operation are all carried out simultaneously.
Corresponding with cataloged procedure, the present invention also provides a kind of SPIHT picture decoding method based on digital signal processor, decode procedure and cataloged procedure completely reversibility, but owing to need the coefficient magnitude of decoding still unknowable, in the initialization of decoding end, do not need the SDL array.As shown in Figure 8, at first carry out the data structure initialization (step 801) of SPIHT picture coding, press bit input information (step 802) from code stream, the sequential scanning state table carries out the bit plane refinement (step 803) of SPIHT coding according to input information then.
The initialization procedure of step 801 comprises: the symbol and the absolute value of wavelet coefficient are separated, and the array of non-important pixel LIP, important pixel LSP and three states of non-important set LIS is represented in initialization.
Because the desorption coefficient size is still unknowable, so do not need as cataloged procedure, to calculate the maximum value bit plane of wavelet coefficient, coding side can pass to decoding end with this information, and the local decode available parameter is transmitted, and the strange land decoding can deposit this information in code stream.
Step 803 comprises:
For important pixel LSP, on the present bit plane, do refinement according to described input information;
For non-important pixel LIP, scan on the present bit plane, according to the threshold value on present bit plane, be re-assigned to LSP or LIP, restore the most significant digit of the coefficient that is assigned to LSP simultaneously, for the refinement decoding of next bit plane is prepared;
For non-important set LIS, the algorithm that non-important pixel collection divides according to zero tree is split into non-important set LIS, non-important pixel LIP and important pixel LSP again according to described input information.
Claims (15)
1, a kind of SPIHT method for encoding images based on digital signal processor is characterized in that comprising the steps:
(1) wavelet coefficient is carried out the data structure initialization of SPIHT picture coding;
(2) compare according to threshold value, judge whether important at the present bit floor coefficient when frontal plane;
(3) sequential scanning state table carries out the bit plane refinement to wavelet coefficient;
(4) bit information of output is spliced and form final code stream.
2, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1 is characterized in that also comprising the steps:
(5) number of bit-planes is subtracted 1, continue coding if desired, then return step (2).
3, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1 is characterized in that the data structure in the described step (1) is a two-dimensional array.
4, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1 is characterized in that the initialization procedure of described step (1) comprising: the maximum value bit plane that calculates wavelet coefficient; Calculate maximum descendants's value of all coefficients that the offspring is arranged; The array of non-important pixel LIP, important pixel LSP and three states of non-important set LIS is represented in initialization, with a unified two-dimensional array state table LIST representative.
5, the SPIHT method for encoding images based on digital signal processor as claimed in claim 4 is characterized in that described LIST two-dimensional array represents the state of adjacent two coefficients in the former matrix of coefficients with a byte, and size is 1/2 of a former matrix of coefficients.
6, the SPIHT method for encoding images based on digital signal processor as claimed in claim 4, it is characterized in that described all have maximum descendants's value of offspring's coefficient to be stored among the two-dimensional array SDL, represent the state that offspring's coefficient is arranged in the former matrix of coefficients with a byte, replace numerical value itself with peaked most significant digit plane.
7, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1, it is characterized in that coefficients by using is by the sequential scan mode of row in the described step (2), with the current line coefficient n of prescan, comprise among capable and the 2nd * n+1 row coefficient of the 2nd * n of all direct offsprings of this row coefficient and corresponding state table LIST, the SDL thereof the place line number and put into internal memory.
8, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1 is characterized in that described step (3) comprising:
The sequential scanning state table in state table, is labeled as the coefficient of important pixel LSP on the present bit plane, will become the some refinement output of important pixel on the present bit plane, exports the corresponding bit information of coefficient in control bit information and the coefficient table simultaneously;
The sequential scanning state table, in state table, be labeled as the coefficient of non-important pixel LIP on the present bit plane, scan on the present bit plane, according to the comparison of present bit plane threshold value, again change the bit of LSP and LIP in the state table, be re-assigned to LSP or LIP, export the corresponding bit information of coefficient in control bit information and the coefficient table simultaneously;
The sequential scanning state table, in state table, be labeled as the coefficient of non-important pixel collection LIS on the present bit plane, will be according to the algorithm of zero tree division, inquire about corresponding SDL with it in showing information and direct offspring's coefficient magnitude, by with the comparison of present bit plane threshold value, judge and be split into non-important set, non-important pixel and important pixel again, revise the corresponding bits position in the LIST state table, export the corresponding bit information of coefficient in control bit information and the coefficient table simultaneously.
9, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1 is characterized in that described step (4) is single-bit or many bits splicing output.
10, the SPIHT method for encoding images based on digital signal processor as claimed in claim 9, it is characterized in that described many bit splicing output, comprise: with some bits elder generation centralized stores in a shaping 32 vbr buffer districts, according to the round-robin implementation status, with function the variable length code in the buffer zone is spliced to output code flow again after reaching certain number.
11, the SPIHT method for encoding images based on digital signal processor as claimed in claim 1, it is characterized in that described SPIHT cataloged procedure is to utilize direct memory visit (DMA) transferring data between the zones of different of storage space, when handling data line, finish the carrying of lastrow or next line data, data carrying and transform operation operation are carried out simultaneously.
12, a kind of SPIHT picture decoding method based on digital signal processor is characterized in that comprising the steps:
(1) carries out the data structure initialization of SPIHT picture coding;
(2) from code stream, press the bit input information;
(3) sequential scanning state table carries out the bit plane refinement of SPIHT coding according to input information.
13, the SPIHT picture decoding method based on digital signal processor as claimed in claim 12, the initialization procedure that it is characterized in that described step (1) comprises: the symbol and the absolute value of wavelet coefficient are separated, and the array of non-important pixel LIP, important pixel LSP and three states of non-important set LIS is represented in initialization.
14, the SPIHT picture decoding method based on digital signal processor as claimed in claim 12 is characterized in that described step (3) comprising:
For important pixel LSP, on the present bit plane, do refinement according to described input information;
For non-important pixel LIP, scan on the present bit plane, according to the threshold value on present bit plane, be re-assigned to LSP or LIP, restore the most significant digit of the coefficient that is assigned to LSP simultaneously, for the refinement decoding of next bit plane is prepared;
For non-important set LIS, the algorithm that non-important pixel collection divides according to zero tree is split into non-important set LIS, non-important pixel LIP and important pixel LSP again according to described input information.
15, the SPIHT picture decoding method based on digital signal processor as claimed in claim 12, it is characterized in that described SPIHT cataloged procedure is to utilize direct memory visit (DMA) transferring data between the zones of different of storage space, when handling data line, finish the carrying of lastrow or next line data, data carrying and transform operation operation are carried out simultaneously.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101015125B (en) * | 2004-06-07 | 2010-04-28 | 新加坡科技研究局 | System and method for scalable encoding and decoding data |
| CN101420608B (en) * | 2007-10-22 | 2011-01-05 | 华为技术有限公司 | Method and device for data decoding implementation |
| CN101980466A (en) * | 2010-11-11 | 2011-02-23 | 北京航空航天大学 | Bit stream transmission method combing SPIHT compression and unequal error protection coding |
| CN101742300B (en) * | 2008-11-21 | 2012-05-09 | 中国科学院空间科学与应用研究中心 | System and method for compressing satellite images with low bit rate |
| CN102473315A (en) * | 2009-08-20 | 2012-05-23 | 汤姆森特许公司 | Method and apparatus for reusing tree structures to encode and decode binary sets |
| CN101639686B (en) * | 2007-06-20 | 2014-06-04 | 爱方有限责任公司 | System and method for interfacing device |
| CN105847846A (en) * | 2010-07-19 | 2016-08-10 | Sk电信有限公司 | Video coding device |
| CN108429916A (en) * | 2018-02-26 | 2018-08-21 | 西安万像电子科技有限公司 | Image encoding method and device |
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2003
- 2003-06-30 CN CN 03148080 patent/CN1255770C/en not_active Expired - Lifetime
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101015125B (en) * | 2004-06-07 | 2010-04-28 | 新加坡科技研究局 | System and method for scalable encoding and decoding data |
| CN101639686B (en) * | 2007-06-20 | 2014-06-04 | 爱方有限责任公司 | System and method for interfacing device |
| CN101420608B (en) * | 2007-10-22 | 2011-01-05 | 华为技术有限公司 | Method and device for data decoding implementation |
| CN101742300B (en) * | 2008-11-21 | 2012-05-09 | 中国科学院空间科学与应用研究中心 | System and method for compressing satellite images with low bit rate |
| CN102473315A (en) * | 2009-08-20 | 2012-05-23 | 汤姆森特许公司 | Method and apparatus for reusing tree structures to encode and decode binary sets |
| CN105847846A (en) * | 2010-07-19 | 2016-08-10 | Sk电信有限公司 | Video coding device |
| CN101980466A (en) * | 2010-11-11 | 2011-02-23 | 北京航空航天大学 | Bit stream transmission method combing SPIHT compression and unequal error protection coding |
| CN101980466B (en) * | 2010-11-11 | 2012-12-12 | 北京航空航天大学 | Bit stream transmission method combing SPIHT compression and unequal error protection coding |
| CN108429916A (en) * | 2018-02-26 | 2018-08-21 | 西安万像电子科技有限公司 | Image encoding method and device |
| CN108429916B (en) * | 2018-02-26 | 2020-07-31 | 西安万像电子科技有限公司 | Image coding method and device |
| CN111316644A (en) * | 2019-02-21 | 2020-06-19 | 上海极清慧视科技有限公司 | Image encoding method, image decoding method, and applicable devices and systems |
| CN111316644B (en) * | 2019-02-21 | 2022-06-28 | 上海极清慧视科技有限公司 | Image encoding method, decoding method, and applicable devices and systems |
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