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Image coding over noisy channels with memory

This paper presents a wavelet-based image coder that is optimized for transmission over binary channels with memory. The proposed coder uses a channel-optimized trellis-coded quantizer (COTCQ) designed for a binary first-order Markov channel. The quantizer stage exploits the channel memory by incorporating the characteristics of the additive correlated channel noise during the quantizer design and by using a new trellis structure. The performance of the proposed memory-optimized COTCQ (MCOTCQ) image coding system is presented for different bit error probabilities and noise correlation parameters. It is shown that the performance of the coder is improved significantly when the second-order statistics of the noise are incorporated at the quantizer design level.