Multiple description coding via polyphase transform and selective quantization

In this paper, we present an efficient Multiple Description Coding (MDC) technique to achieve robust communication over unreliable channels such as a lossy packet network. We first model such unreliable channels as erasure channels and then we present a MDC system using polyphase transform and selective quantization to recover channel erasures. Different from previous MDC work, our system explicitly separates description generation and redundancy addition which greatly reduces the implementation complexity specially for systems with more than two descriptions. Our system also realizes a Balanced Multiple Description Coding (BMDC) framework which can generate descriptions of statistically equal rate and importance. This property is well matched to communication systems with no priority mechanisms for data delivery, such as today's Internet. We then study, for a given total coding rate, the problem of optimal bit allocation between source coding and redundancy coding to achieve the minimum average distortion for different channel failure rates. With high resolution quantization assumption, we give optimal redundancy bit rate allocations for both scalar i.i.d sources and vector i.i.d sources for independent channel failures. To evaluate the performance of our system, we provide an image coding application with two descriptions and our simulation results are better than the best MDC image coding results reported to date. We also provide image coding examples with 16 descriptions to illustrate the simplicity and effectiveness of our proposed MDC system.