Rate-Distortion Performance of Several Joint Source and Channel Coding Schemes for Images

Abstract

This paper describes a methodology for evaluating the rate-distortion behavior of combined source and channel coding schemes with particular application to images. We demonstrate use of the operational rate-distortion function to obtain the optimum tradeoff between source coding accuracy and channel error protection under the constraint of a fixed transmission bandwidth. Furthermore, we develop information-theoretic bounds on performance and demonstrate that our combined source-channel coding methodology results in rate-distortion performance which closely approaches these theoretical limits. We concentrate specifically on a wavelet-based subband source coding scheme followed by either a scalar quantizer or a product pyramid vector quantizer (PPVQ) and the use of binary rate-compatible punctured convolutional (RCPC) codes for transmission over the additive white Gaussian noise (AWGN) channel.KeywordsAdditive White Gaussian NoiseChannel CapacityChannel CodeChannel ErrorScalar QuantizerThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.