Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/293
Title: New adaptive partial distortion search using clustered pixel matching error characteristic
Authors: Hui, Ko-cheung
Siu, Wan-chi
Chan, Yui-lam
Subjects: Motion estimation
Partial distortion search (PDS)
Video coding
Issue Date: May-2005
Publisher: IEEE
Source: IEEE transactions on image processing, May 2005, v. 14, no. 5, p. 597-607
Abstract: In order to reduce the computation load, many conventional fast block-matching algorithms have been developed to reduce the set of possible searching points in the search window. All of these algorithms produce some quality degradation of a predicted image. Alternatively, another kind of fast block-matching algorithms which do not introduce any prediction error as compared with the full-search algorithm is to reduce the number of necessary matching evaluations for every searching point in the search window. The partial distortion search (PDS) is a well-known technique of the second kind of algorithms. In the literature, many researches tried to improve both lossy and lossless block-matching algorithms by making use of an assumption that pixels with larger gradient magnitudes have larger matching errors on average. Based on a simple analysis, it is found that, on average, pixel matching errors with similar magnitudes tend to appear in clusters for natural video sequences. By using this clustering characteristic, we propose an adaptive PDS algorithm which significantly improves the computation efficiency of the original PDS. This approach is much better than other algorithms which make use of the pixel gradients. Furthermore, the proposed algorithm is most suitable for motion estimation of both opaque and boundary macroblocks of an arbitrary-shaped object in MPEG-4 coding.
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Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/293
DOI: 10.1109/ISCAS.2004.1329217
ISSN: 1057-7149
Appears in Collections:EIE Journal/Magazine Articles

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