Combating Packet Loss in Image Coding using Oversampling and Irregular Interpolation

Diversity “multiple description” (MD) source coding promises graceful degradation in the presence of an unknown number of erasures in the channel. A simple solution in 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 into two packets 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 do not form a uniform sampling pattern. In this work we show how noise amplification can be reduced by optimizing the interpolation filter. We propose two interpolation methods which, for a given total coding rate, minimize the average distortion over all (K out of N) patterns of received packets. We provide simulation results comparing low pass and irregular interpolation filters, and discuss the advantage of each method.