Fast block matching algorithm based on the winner-update strategy

Block matching is a widely used method for stereo vision, visual tracking, and video compression. Many fast algorithms for block matching have been proposed in the past, but most of them do not guarantee that the match found is the globally optimal match in a search range. This paper presents a new...

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Vydáno v:IEEE transactions on image processing Ročník 10; číslo 8; s. 1212 - 1222
Hlavní autoři: CHEN, Yong-Sheng, HUNG, Yi-Ping, FUH, Chiou-Shann
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.08.2001
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Applied sciences
Artificial intelligence
Blocking
Computational efficiency
Computer science
Computer science; control theory; systems
Errors
Exact sciences and technology
HTML
Image processing
Information science
Information, signal and communications theory
Lists
Lower bounds
Matching
Mathematical analysis
Motion estimation
Optimal matching
Pattern recognition. Digital image processing. Computational geometry
Pixel
Searching
Signal processing
Stereo vision
Studies
Telecommunications and information theory
Testing
Video compression
Motion estimation
Image processing
Minkowski metric
Data compression
Video signal
Image compression
Fast algorithm
Block matching
ISSN:1057-7149, 1941-0042
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Popis
Shrnutí:Block matching is a widely used method for stereo vision, visual tracking, and video compression. Many fast algorithms for block matching have been proposed in the past, but most of them do not guarantee that the match found is the globally optimal match in a search range. This paper presents a new fast algorithm based on the winner-update strategy which utilizes an ascending lower bound list of the matching error to determine the temporary winner. Two lower bound lists derived by using partial distance and by using Minkowski's inequality are described. The basic idea of the winner-update strategy is to avoid, at each search position, the costly computation of the matching error when there exists a lower bound larger than the global minimum matching error. The proposed algorithm can significantly speed up the computation of the block matching because (1) computational cost of the lower bound we use is less than that of the matching error itself; (2) an element in the ascending lower bound list will be calculated only when its preceding element has already been smaller than the minimum matching error computed so far; (3) for many search positions, only the first several lower bounds in the list need to be calculated. Our experiments have shown that, when applying to motion vector estimation for several widely-used test videos, 92% to 98% of operations can be saved while still guaranteeing the global optimality. Moreover, the proposed algorithm can be easily modified either to meet the limited time requirement or to provide an ordered list of best candidate matches.
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ISSN:1057-7149
1941-0042
DOI:10.1109/83.935037