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Proceedings Paper

Jointly optimal forward-backward motion compensated prediction for video signals
Author(s): Rajesh Rajagopalan; Michael T. Orchard
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Paper Abstract

Motion compensation of video has been studied within two general frameworks: forward prediction in which motion parameters are computed at the encoder and transmitted over the channel, and backward prediction in which motion parameters are computed at the decoder. Recent work has proposed a promising hybrid forward-backward approach (some parameters are transmitted -- others are computed at the decoder) that exploits the best features of both approaches. However, the forward information used in that work consisted of standard block matching motion vectors and that work did not address how to optimize motion parameters in the context of both forward and backward information. In this work, we propose a jointly optimal forward-backward motion compensation approach. Applications of our approach to inter-frame prediction and denoising are presented. Experimental results demonstrate the excellent performance gains, in particular, prediction efficiency improves by 26% on the average compared to block matching at half-pel accuracy and denoising performance is close to optimal.

Paper Details

Date Published: 27 February 1996
PDF: 9 pages
Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); doi: 10.1117/12.233277
Show Author Affiliations
Rajesh Rajagopalan, Princeton Univ. (United States)
Michael T. Orchard, Princeton Univ. (United States)


Published in SPIE Proceedings Vol. 2727:
Visual Communications and Image Processing '96
Rashid Ansari; Mark J. T. Smith, Editor(s)

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