A Scalable Distributed Video Coder Using Compressed Sensing

Distributed Video Coding (DVC) is a new paradigm for video compression, which is particularly attractive due to its flexibility to introduce very simple encoder structure. However, most DVC systems are unable to adapt to the bandwidth variations. In this paper we propose a scalable DVC scheme, which can adjust the bit-rate linearly depending on the available bandwidth, and thereby achieves optimal quality of service (QoS). Our algorithm combines compressed sensing with multiple measurement vectors problem to achieve significantly low encoding complexity. The correlation structure in the successive video frames is exploited by joint sparsity, which in turn helps reduce decoding complexity. The simulation results depict a significantly improved performance over other low complexity video codec schemes.