Maximum likelihood estimation for the generation of side information in distributed video coding
 
Maximum likelihood estimation for the generation of side information in distributed video coding 
 
Frederik Verbist, Frederik Verbist, Nikos Deligiannis, Nikos Deligiannis, Marc Jacobs, Marc Jacobs, Joeri Barbarien, Joeri Barbarien, Peter Schelkens, Peter Schelkens, Adrian Munteanu, Adrian Munteanu, Jan Cornelis, Jan Cornelis
 
Abstract 

The unique requirements imposed by contemporary video communication applications promote the rise of the distributed video coding paradigm, which offers flexible complexity allocation and error resilience combined with competitive compression performance. This work proposes a novel Wyner-Ziv video coding scheme, performing hash-based motion estimation at the decoder. Subsequently, maximum likelihood estimation generates side information from a collection of candidate predictor values. Moreover, a supplemental Wyner-Ziv enhancement layer is coded in the transform domain. The presented Wyner-Ziv coding scheme delivers state-of-the-art compression performance, achieving average Bj{\o}ntegaard rate savings of up to 9.31\% compared to a state-of-the-art reference codec.