Combating Packet Loss in Image Coding Using Oversampling, Irregular Interpolation and Noise Shaping

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.