Applying data mining techniques in a Wyner-Ziv to H.264 video transcoder

Authors:
José Luis Martínez;Alberto Corrales-García;Pedro Cuenca;Francisco José Quiles
Affiliations:
Architecture and Technology of Computing Systems Group, Complutense University, Madrid, Spain;Instituto de Investigación en Informática de Albacete (I3A), University of Castilla-La Mancha, Albacete, Spain;Instituto de Investigación en Informática de Albacete (I3A), University of Castilla-La Mancha, Albacete, Spain;Instituto de Investigación en Informática de Albacete (I3A), University of Castilla-La Mancha, Albacete, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Year:
2011

Citing 3
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Abstract

This paper proposes an improved Wyner-Ziv to H.264 transcoder for supporting mobile-to-mobile video communications. In this framework, both transmitter and receptor should employ video encoders and decoders of low complexity. Taking advantage of both paradigms, in terms of low complexity algorithms, a suitable solution consists in transcoding from Wyner-Ziv to H.264. In order to reduce this process this paper proposes an algorithm which is based on the hypothesis that macroblock coding mode decisions in H.264 video have a high correlation with the distribution of the side information residual in Wyner-Ziv video. The proposed algorithm, which is based on data mining techniques, selects one sub-set of the several coding modes in H.264. Simulation results show that the proposed transcoder reduces the inter prediction complexity in H.264 by up to 53%, while maintaining coding efficiency.