Jointly optimal forward-backward motion-compensated prediction for video signals

Rajesh Rajagopalan; Michael T. Orchard

doi:10.1117/12.233277

27 February 1996 Jointly optimal forward-backward motion compensated prediction for video signals

Rajesh Rajagopalan, Michael T. Orchard

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233277
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

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.

Citation Download Citation

Rajesh Rajagopalan and Michael T. Orchard "Jointly optimal forward-backward motion compensated prediction for video signals", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233277

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