Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tsai, Jang-Jer | en_US |
dc.contributor.author | Hang, Hsueh-Ming | en_US |
dc.date.accessioned | 2014-12-08T15:09:35Z | - |
dc.date.available | 2014-12-08T15:09:35Z | - |
dc.date.issued | 2007 | en_US |
dc.identifier.isbn | 978-1-4244-0920-4 | en_US |
dc.identifier.issn | 0271-4302 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/7334 | - |
dc.identifier.uri | http://dx.doi.org/10.1109/ISCAS.2007.378545 | en_US |
dc.description.abstract | Pattern-based block motion estimation (PBME) is one of the most effective yet computational intensive tools in digital video coding standards. Many PBME algorithms have been proposed but few papers have investigated in depth the fundamental characteristics of various PBME algorithms. Why one search algorithm outperforms the others? In this paper, we propose a systematic approach to examine this problem. The minimal numbers of search points achievable by a PBME algorithm form a discrete function in the search area. We analyze this so-called weighting function and suggest an ideal target. Then, we design a genetic rhombus pattern search (GRPS) to match this ideal weighting function. Simulations show that comparing to the other popular search algorithms, GRPS reduces the average search points for more than 20% while it maintains a similar level of coded image PSNR quality. | en_US |
dc.language.iso | en_US | en_US |
dc.title | A genetic rhombus pattern search for block motion estimation | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ISCAS.2007.378545 | en_US |
dc.identifier.journal | 2007 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-11 | en_US |
dc.citation.spage | 3655 | en_US |
dc.citation.epage | 3658 | en_US |
dc.contributor.department | 電子工程學系及電子研究所 | zh_TW |
dc.contributor.department | Department of Electronics Engineering and Institute of Electronics | en_US |
dc.identifier.wosnumber | WOS:000251608405001 | - |
Appears in Collections: | Conferences Paper |
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