CN1281065C - Tree-structure-based grade tree aggregation-divided video image compression method - Google Patents

Tree-structure-based grade tree aggregation-divided video image compression method Download PDF

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CN1281065C
CN1281065C CN 200410018507 CN200410018507A CN1281065C CN 1281065 C CN1281065 C CN 1281065C CN 200410018507 CN200410018507 CN 200410018507 CN 200410018507 A CN200410018507 A CN 200410018507A CN 1281065 C CN1281065 C CN 1281065C
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tree
code stream
coding
threshold value
wavelet
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CN1581977A (en
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华赟
胡波
徐晟�
高佳
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Fudan University
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Fudan University
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Abstract

The present invention relates to a grade tree aggregation-divided (SPIHT) method for compressing a video image compression, which is based on a tree structure. Through discrete wavelet transformation, a coding end first obtains distribution of image energy on a time frequency field. According to correlation between wavelet coefficients, a wavelet coefficient of each grade is divided according to a tree structure. Then, SPIHT coding operation is carried out for the wavelet coefficient of each tree, and coding results are respectively and temporarily stored at the coding end. Finally, coding results of the trees are synthesized to a code stream for storage or transportation. A decoding course is the inverse course of the coding course. Under the precondition of no consumption of excess calculation amount, the present invention greatly saves memory usage in a calculating course. Thus, the present invention is suitable for real-time and high-efficiency compression for a video stream, and is particularly suitable for a dedicated system for hardware implementation, which means video compression with a high compression ratio and a low distortion factor can be realized by means of less storage space.

Description

Video image compressing method is divided in hierarchical tree set based on tree
Technical field
The invention belongs to the video image compression technology field, be specifically related to a kind of hierarchical tree set and divide video image compressing method based on tree.
Background technology
Hierarchical tree set division (SPIHT) algorithm has taken into full account the correlation between the data, and has considered that also the higher bit data importance is higher than the characteristic of hanging down Bit data in the same data when coding.So use the distortion factor that the SPIHT method is compressed, the decompressed video image can obtain not increasing than higher compression ratio the decompression result, so this method has received increasingly extensive concern.In the process of specific implementation, coded system need be set up three chained lists, promptly important pixel chained list (LSP), inessential pixel chained list (LIP) and inessential pixel set chained list (LIS), and these three chained lists are used for writing down the intermediate data of tree division.By the use of chained list, the sequence arrangement that encoding code stream can descend according to threshold value (importance), thus guarantee the transmission of important information and can block non-important information, blocked the compression effectiveness of the high compression ratio of code stream arbitrarily.In order to improve compression effectiveness, require tree to comprise more data.But along with the increase of data volume in the tree, the length of three chained lists is just more and more longer, just requires huge memory headroom in actual applications, and this has just increased the cost and the complexity of system.So under the prerequisite that does not reduce compression effectiveness, the method that shortens chained list length is just becoming the focus of research.
Summary of the invention
The objective of the invention is to propose a kind of hierarchical tree set and divide (SPIHT) video image compressing method,, save the memory headroom expense of system to guarantee shortening the length of chained list greatly under the prerequisite that compression effectiveness do not descend based on tree.
(SPIHT) video image compressing method is divided in the hierarchical tree set based on tree that the present invention proposes, the concrete steps of coding are as follows: at first by wavelet transform obtain image energy the time distribution on the frequency domain, because the flatness of image, image energy concentrates on low frequency part; According to the correlation between the wavelet coefficient, wavelet coefficient at different levels is divided according to tree; Wavelet coefficient to every tree carries out the SPIHT coding respectively then, and coding result temporarily leaves coding side respectively in; At last the coding result of every tree is synthesized a code stream and be used for storage or transmission.
According to the data dependence between the wavelet coefficient, it is tree root that wavelet coefficient at different levels is divided each coefficient that is meant with the lowest frequency subband according to tree, obtains the data of each point in the tree according to the data dependence of wavelet coefficient position between the different stage.In the tree, the relation between upper level wavelet coefficient and the next stage wavelet coefficient is called father and mother and children or offspring's relation.In wavelet coefficient, the coefficient of different sub-band same position, similitude is often numerically arranged, according to such relation, with each coefficient of lowest frequency subband root node as tree, the coefficient of same position is as the first order children of tree in the higher leveled filial generation, with the coefficient of children's same position of each first order children as first order children, also is the second level children of tree in the more higher leveled filial generation ... up to the coefficient of high-frequency sub-band children as afterbody.
Wavelet coefficient to every tree carries out the SPIHT coding respectively, can reduce simultaneously treated wavelet coefficient, the intermediate object program that produces is less, has shortened the length of important pixel chained list (LSP), inessential pixel chained list (LIP) and inessential pixel set chained list (LIS).Its method is exactly that the coding result of every tree is all obtained successively according to the order that threshold value descends, up to threshold value drop to can satisfy compression and require till.The prediction threshold value decision that the threshold value falling-threshold can be obtained by the minimum threshold or the empirical value of former frame group.The result that the wavelet coefficient of every tree carries out SPIHT coding will not directly be transmitted, but is temporarily stored in coding side, when depositing the encoding code stream under each threshold value situation is deposited successively, and is write down encoding code stream length under each threshold value situation.
After the wavelet coefficient end-of-encode of all trees,, need the coding result of every tree is synthesized the target code stream in order to obtain meeting the target code stream of compression ratio requirement.The method of synthetic code stream is to determine minimum threshold value, be called interceptive value, make the code stream sum that is not less than this threshold value in every tree-encoding code stream be not more than target code stream length, these encoding code streams and code stream length are synthesized the target code stream, and remaining target code stream is again by all the other encoding code stream mean allocation of every tree.The length that exactly threshold value among every tree-encoding result is not less than the code stream of interceptive value and these code streams is directly as the target code stream, the part of target code stream deficiency by threshold value among every tree-encoding result less than the code stream mean allocation of interceptive value.
Depositing of the division that focuses on tree of cataloged procedure, tree wavelet coefficient coding result and synthesizing of target code stream.
In decoding end, decode procedure is the inverse process of cataloged procedure: the buffer memory of at first code stream to be decoded being distributed to every tree, the code stream that every tree is assigned to carries out the SPIHT decoding successively again, obtain the wavelet coefficient of tree, wavelet coefficient with tree is reduced to the wavelet coefficient of arranging by subband again, obtains decoded picture by wavelet inverse transformation.
(SPIHT) video image compressing method is divided in hierarchical tree set based on tree proposed by the invention, has effectively solved the contradiction between image data amount and the chained list length.In order to improve compression effectiveness, the image (frame group) of multiframe can be carried out wavelet transform together, make every tree can comprise abundant wavelet coefficient; Because every tree is encoded respectively, can't cause the excessive lengthening of important pixel chained list (LSP), inessential pixel chained list (LIP) and inessential pixel set chained list (LIS) length.
Description of drawings
Fig. 1 is root node and first three searching relation for children.
Fig. 2 is the relation that back two generation children seek.
Embodiment
Below to the invention in each composition discussed respectively.
1. wavelet transform result's tree is divided
Wavelet transform can use three-dimensional wavelet transform, promptly carries out wavelet transform respectively at line direction, column direction and time orientation.Each coefficient of the lowest frequency of transformation results is as the root node of one tree, and according to relation of plane down, constitutes tree.The size of supposing the lowest frequency coefficient is W Min* H Min, W wherein MinAnd H MinBe respectively the width and the height of the lowest frequency subband of lowest frequency frame.
1) its children of root node children finding method are;
( x , y , z ) ( x + W min , y , z ) , ( x , y + H min , z ) , ( x + W min , y + H min , z ) , ( x , y , z + 1 ) , ( x + W min , y , z + 1 ) , ( x , y + H min , z + 1 ) , ( x + W min , y + H min , z + 1 ) - - - ( 1 )
2) two-dimentional its children of children's finding method are:
( x , y , z ) ( 2 x , 2 y , z ) , ( 2 x + 1,2 y , z ) , ( 2 x , 2 y + 1 , z ) , ( 2 x + 1,2 y + 1 , z ) - - - ( 2 )
3) three-dimensional its children of children's finding method are:
( x , y , z ) ( 2 x , 2 y , 2 z ) , ( 2 x + 1,2 y , 2 z ) , ( 2 x , 2 y + 1,2 z ) , ( 2 x + 1,2 y + 1,2 z ) , ( 2 x , 2 y , 2 z + 1 ) , ( 2 x + 1,2 y , 2 z + 1 ) , ( 2 x , 2 y + 1 , 2 z + 1 ) , ( 2 x + 1,2 y + 1,2 z + 1 ) - - - ( 3 )
Illustrated in figures 1 and 2, Fig. 1 represents is root node and first three searching relation for children, what Fig. 2 represented is the relation that back two generation children seek, in seven branches of only having drawn among the figure one.
2. every tree wavelet coefficient SPIHT coding result deposits
D M, NThe expression threshold value is from 2 N+1Drop to 2 NThe time M the tree threshold value be the coded data of N.L M, NThe expression threshold value is from 2 N+1Drop to 2 NThe time M the tree threshold value be the coded data length of N.The form that the coding result of all trees is deposited is as follows:
Threshold value 2 N 2 N-1 …… 2 -1
The 1st tree D 1,N D 1,N-1 …… D 1,-1
The 2nd tree D 2,N D 2,N-1 …… D 2,-1
The 3rd tree D 3,N D 3,N-1 …… D 3,-1
M tree D M,N D M,N-1 …… D M,-1
3. the target code stream is synthetic
If M tree arranged, the target code stream length of requirement is Q.Drop to 2 in threshold value PThe time, total code stream length of all trees is
N 1 = Σ n = 1 M Σ m = P N L n , m , Drop to 2 in threshold value P-1The time, total code stream length of all trees is N 2 = Σ n = 1 M Σ m = P - 1 N L n , m , And satisfy N 1<Q≤N 2, so 2 PBe interceptive value.Earlier M tree threshold value dropped to 2 PThe time all code streams and code stream length as the target code stream, if the code stream length of every tree target approach code stream will represent that this moment, the target code stream was about N with the X bit 1+ X is again with remaining Q-N 1The object code levelling of-X all is assigned in M the tree in remaining encoding code stream, is 2 with every tree threshold value just P-1Preceding (Q-N 1-X)/the M code stream is as the target code stream.Specifically in the target code stream, the encoding code stream of each tree is to arrange like this:
The 1st tree Σ m = P N L 1 , m , D 1 , N - D 1 , P ;
The 2nd tree Σ m = P N L 2 , m , D 2 , N - D 2 , P ;
……
M tree Σ m = P N L M , m , D M , N - D M , P ;
D 1, P-1In the 1st bit; D 2, P-1In the 1st bit; D M, P-1In the 1st bit;
D 1, P-1In the 2nd bit; D 2, P-1In the 2nd bit; D M, P-1In the 2nd bit;
……
Reach requirement up to target code stream length.
The process of decoding is entirely the inverse process of coding.At first code stream to be decoded is distributed to the buffer memory of every tree, the code stream that every tree is assigned to carries out the SPIHT decoding successively again, obtain the wavelet coefficient of tree, the wavelet coefficient with tree is reduced to the wavelet coefficient of arranging by subband again, obtains decoded picture by wavelet inverse transformation.
The result of emulation
Concrete simulated conditions is as follows:
The Y Value Data of Miss American video image group 1-8 two field picture, every two field picture size is 352 * 288.Carry out three grades of 3 d-dem wavelet transformations, again low-frequency frame is carried out the two-stage two-dimensional discrete wavelet conversion, wavelet basis is selected Daubechies9/7 biorthogonal wavelet (line direction and column direction) and Haar small echo (time orientation) for use.Have 99 trees.
Experimental result is as follows:
Original image 8 frames, 352 * 288Y value Totally 811008 bytes
The wavelet transformation result Each wavelet coefficient is represented with 16bits Totally 1622016 bytes
Every tree A frame component is 99 trees Totally 16384 bytes
Compression multiple/target code stream length Index Before the optimization After the optimization *
200/4055 byte LIP chained list length 6642 4433
LSP chained list length 6084 6459
LIS chained list length 3521 536
The PSNR effect 39.3690 39.0733
150/5406 byte LIP chained list length 10752 4429
LSP chained list length 7851 6419
LIS chained list length 4651 536
The PSNR effect 39.9526 39.5110
100/8110 byte LIP chained list length 14384 4443
LSP chained list length 12134 6448
LIS chained list length 5216 536
The PSNR effect 40.7056 40.4405
50/16220 byte LIP chained list length 44952 4390
LSP chained list length 22792 6462
LIS chained list length 13988 536
The PSNR effect 41.4691 41.3303
*LIP after the optimization, LIP, LIS are length maximum in 99 trees, and every tree-encoding all proceeds to threshold value and reduce to till 8, and the evidence threshold value drops to 8, generally just can satisfy the requirement of compression ratio.
We find by result of upper experiment, though the result of this SPIHT coding method has reduced PSNR (reducing very for a short time), the space that is used to store chained list can reduce greatly.

Claims (3)

  1. Video image compressing method is divided in 1 one kinds of hierarchical tree set based on tree, it is characterized in that by wavelet transform obtain image energy the time distribution on the frequency domain, wavelet coefficient at different levels is divided according to tree: each coefficient with the lowest frequency subband is a tree root, obtains the data of each point in the tree according to the data dependence of wavelet coefficient position between the different stage again; Wavelet coefficient to every tree carries out hierarchical tree set division coding respectively then, coding result is temporarily deposited respectively, at last the coding result of every tree is synthesized a code stream and be used for storage or transmission, wherein, the method of synthetic code stream is to determine minimum threshold value, make the code stream sum that is not less than this threshold value in every tree-encoding code stream be not more than target code stream length, these encoding code streams and code stream length is synthetic as the target code stream, and remaining target code stream is again by all the other encoding code stream mean allocation of every tree.
  2. Video image compressing method is divided in the 2 hierarchical tree set based on tree according to claim 1, it is characterized in that every tree all carries out the hierarchical tree set respectively and divides coding, the coding result of every tree all obtains according to the order that threshold value descends, up to threshold value drop to can satisfy compression and require till.
  3. Video image compressing method is divided in the 3 hierarchical tree set based on tree according to claim 1 and 2, the coding result that it is characterized in that every tree is temporarily stored in coding side earlier, when depositing the encoding code stream under each threshold value situation is deposited successively, and write down encoding code stream length under each threshold value situation.
CN 200410018507 2004-05-20 2004-05-20 Tree-structure-based grade tree aggregation-divided video image compression method Expired - Fee Related CN1281065C (en)

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CN100435550C (en) * 2006-05-10 2008-11-19 北京好望角医学影像技术有限公司 Method for increasing anti-bit-error ability of grade-tree collecting splitting algorithm coding-decoding device
CN101783939B (en) * 2009-01-16 2012-08-22 复旦大学 Picture coding method based on human eye visual characteristic
EP2467829A1 (en) * 2009-08-20 2012-06-27 Thomson Licensing Method and apparatus for reusing tree structures to encode and decode binary sets
PT3703377T (en) 2010-04-13 2022-01-28 Ge Video Compression Llc Video coding using multi-tree sub-divisions of images
KR102080450B1 (en) 2010-04-13 2020-02-21 지이 비디오 컴프레션, 엘엘씨 Inter-plane prediction
KR101556821B1 (en) 2010-04-13 2015-10-01 지이 비디오 컴프레션, 엘엘씨 Inheritance in sample array multitree subdivision
PT2559246T (en) 2010-04-13 2016-09-14 Ge Video Compression Llc Sample region merging
CN102572423B (en) * 2011-12-16 2014-12-03 辽宁师范大学 Video coding method based on important probability balanced tree
CN110583288A (en) * 2019-10-15 2019-12-20 西安石油大学 Mobile landscaping ecological information processing system and method

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