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Content Provider | IEEE Xplore Digital Library |
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Author | Jun Zhu Binglian Zhu |
Copyright Year | 2007 |
Description | Author affiliation: Univ. of Chongqing, Chongqing (Jun Zhu; Binglian Zhu) |
Abstract | In this paper, a novel fast block-matching algorithm (BMA) for motion estimation is proposed, named fast block-matching motion estimation algorithm based on artificial immune system (AIS). This algorithm inspired from immunology can effectively overcome the inherent drawback of being liable to get trapped in local optima in traditional fast BMAs such as TSS and DS. In the meantime, we proposed an improved immune selection approach based on antibody suppression to reduce computational complexity. Moreover, the immune memory mechanism is utilized in AIS to improve search performance further. The experimental results demonstrate that the proposed AIS outperforms TSS and DS in searching quality at comparable computational cost, which takes a better tradeoff between exploration and exploitation. |
Starting Page | 579 |
Ending Page | 583 |
File Size | 192355 |
Page Count | 5 |
File Format | |
ISBN | 1424410916 |
DOI | 10.1109/ICITECHNOLOGY.2007.4290383 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-03-20 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Pathogens Motion estimation Cloning Block-matching algorithm Educational institutions Computational complexity global optimization Artificial immune systems motion estimation Computational efficiency Space exploration Computational intelligence Immune system artificial immune system |
Content Type | Text |
Resource Type | Article |
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