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Proceedings Paper

Analysis of motion-compensated temporal filtering versus motion-compensated prediction
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Paper Abstract

In previous work, a performance bound for multi-hypothesis motion-compensated prediction (MCP) has been derived based on a video signal model with independent Gaussian displacement errors. A simplified form of the result is derived in this work. A performance bound for optimal motion-compensated temporal filtering (MCTF) has also been proposed based on a signal model with correlated Gaussian displacement errors. In this previous work, the optimal MCTF (KLT) was found to perform better than one-hypothesis MCP but not better than infinite-hypothesis MCP. In this work, we derive the performance of multi-hypothesis MCP again based on the signal model with correlated Gaussian displacement errors. Now with the same signal model, we find that optimal MCTF has the same performance as that of infinite-hypothesis MCP.

Paper Details

Date Published: 14 March 2005
PDF: 6 pages
Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); doi: 10.1117/12.584175
Show Author Affiliations
Yongjun Wu, Rensselaer Polytechnic Institute (United States)
John W. Woods, Rensselaer Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 5685:
Image and Video Communications and Processing 2005
Amir Said; John G. Apostolopoulos, Editor(s)

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