Multiple Description Coding: Proposed Methods And Video Application

Multiple description (MD) coding and quantization has received a lot of attention recently, and has been studied extensively and extended to many demanding appli-cations such as speech and video. We propose two multiple description quantization schemes in order to design the codebooks and partitions of side and central quantiz-ers. The applied framework originates in the multiple description quantization via Gram-Schmidt orthogonalization approach which provides systematic treatment of the achievable rate-distortion region by subtractive dithering and successive quanti-zation along with quantization splitting. The basic idea of our proposed MD quanti-zation schemes is to minimize a Lagrangian cost function (defined as the weighted sum of the central and side distortions) by an iterative technique which jointly designs side codebooks and consequently forms associated partitions. In the first scheme, multiple description vector quantization with weighted sum central decoder (MDVQ-WSC), the central decoder is formed by a linear combination (weighted sum) of the side codebooks. The parameters of this linear combination are also found to minimiz