Distributed Source Coding With Context Modeling

Abstract

We introduce context modeling into the distributed source coding (DSC). By forming contexts from prior coded bitplanes of both the reference and DSC coded peer, we split the virtual channel between the two correlated bitplanes into several virtual sub-channels of different characteristics. The selection of the sub-channel becomes side information that is known to the receiver. As a result, the DSC coding bitrate is reduced. We also investigate a number of practical implementation issues in DSC; e.g., the use of turbo-based channel code vs. the LDPC-based channel code, and the use of a random flipper to handle the binary asymmetric channel. We implemented a practical DSC audio coding system. We show that DSC without context modeling shows little performance gain compared with separate source coding with context modeling. In comparison, context DSC achieves an overall rate saving of 36%, even as we only applied DSC on a selected number of bitplanes, and considering the channel code loss in practical implementation