Robust video transmission using Layered Compressed Sensing

• Published in: 2009 IEEE 11th International Workshop on Multimedia Signal Processing pp. 1 - 4
• Main Authors: Do, T.T., Yi Chen, Nguyen, D.T., Nguyen, N., Lu Gan, Tran, T.D.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2009
• Subjects: Compressed sensing; Decoding; Distributed video coding; Error analysis; Loss measurement; Propagation losses; Protection; Robustness; side information; Source coding; sparse recovery; Streaming media; systematic lossy source/channel coding; Video compression; Wyner-Ziv coding
• ISBN: 9781424444632; 1424444632
• DOI: 10.1109/MMSP.2009.5293312

We propose a novel layered compressed sensing (CS) approach for robust transmission of video signals over packet loss channels. In our proposed method, the encoder consists of a base layer and an enhancement layer. The base layer is a conventionally encoded bitstream and transmitted without any error protection. The additional enhancement layer is a stream of compressed measurements taken across slices of video signals for error-resilience. The decoder regards the corrupted base layer as the side information (SI) and employs a sparse recovery with SI to recover approximation of lost packets. By exploiting the SI at the decoder, the enhancement layer is required to transmit a minimal amount of compressed measurements for error protection that is only proportional to the amount of lost packets. Simulation results show that both compression efficiency and error-resilience capacity of the proposed scheme are competitive with those of other state-of-the-art robust transmission methods, in which Wyner-Ziv (WZ) coders often generate an enhancement layer. Thanks to the soft-decoding feature of sparse recovery algorithms, our CS-based scheme can avoid the cliff effect that often occurs with other Wyner-Ziv based schemes when the error rate is over the error correction capacity of the channel code. In addition, our result suggests that compressed sensing is actually closer to source coding with decoder side information than to conventional source coding.