Multiple-description image coding with distributed source coding and side information

Multiple description coding (MDC) is a source coding technique that involves coding the source information into multiple descriptions. When these descriptions are transmitted over different channels in packet network or error-prone wireless environment, graceful degradation can be achieved even if part of descriptions are not received by the receiver. When MDC is applied to wavelet subband based image coding, it is possible to introduce correlation between the descriptions in each subband. In this paper, we consider using such a correlation as well as potentially error corrupted description as side information in the decoding to formulate the MDC decoding as a Wyner Ziv decoding problem. If only part of descriptions is lost, however, their correlation information is still available. Therefore, the proposed Wyner Ziv decoder can recover the description by using the correlation information and the error corrupted description as side information. High quality reconstruction can still be obtained by combining the decoded descriptions from Wyner Ziv decoder. The proposed scheme takes advantage of an efficient way to use the correlation information, thus makes the system more robust to channel error corruption. Experimental result shows that, comparing to conventional multiple description wavelet based image coding, the PSNR of the received and decoded image could be improved noticeably when coding at the same bit rate.