Diversity "multiple description" (MD) source coding promises graceful degradation in the presence of a priori unknown number of erased packets in the channel. A simple coding scheme for the case of two packets consists of oversampling the source by a factor of two and delta-sigma quantization. This approach was applied successfully to JPEG-based image coding over a lossy packet network, where the interpolation and splitting into two descriptions are done in the discrete cosine transform (DCT) domain. Moreover, unlike the classical source-channel separation approach - which is designed for a predetermined number of erasures (say, K out of N ), hence its distortion does not improve when the channel behaves better than expected - an MD coding scheme aims to achieve a better reconstruction quality when more or all the N descriptions are received at the decoder side. The extension to a larger number of descriptions, however, suffers from noise amplification whenever the received descriptions form a non-uniform sampling pattern. In this work, we examine inter- and intra-block interpolation methods, and show how noise amplification can be reduced by redesigning the interpolation filter at the encoder. Specifically, for a given total coding rate, we demonstrate that an "irregular" interpolation filter is robust to the pattern of received packets over all ( K out of N ) patterns, with some degradation relative to low-pass (LP) interpolation in the case where all N packets arrived. We provide experimental results comparing LP and irregular interpolation filters, and examine the effect of noise shaping on the trade-off between the central distortion (receiving all packets) and side distortion (receiving K packets).

Diversity "multiple description" (MD) source coding promises graceful degradation in the presence of an unknown number of erasures in the channel. A simple scheme for the case of two descriptions consists of oversampling the source by a factor of two and delta-sigma quantization. This approach was applied successfully to JPEG-based image coding over a lossy packet network, where the interpolation and splitting into two descriptions is done in the discrete cosine transform (DCT) domain. The extension to a larger number of descriptions, however, suffers from noise amplification whenever the received descriptions form a nonuniform sampling pattern. In this work, we examine inter and intra-block interpolation methods and show how noise amplification can be reduced by optimizing the interpolation filter. Specifically, for a given total coding rate, we demonstrate that an irregular interpolation filter minimizes the average distortion over all (K out of N) patterns of received packets, ("side receivers"). We provide experimental results comparing low-pass (LP) and irregular interpolation filters for the side receivers and the all-N central receiver. We further examine the effect of noise shaping on the trade-off between the central and side distortions.