Optimal block cosine transform image coding for noisy channels

A method is presented for the joint source-channel coding optimization of a scheme based on the two-dimensional block cosine transform when the output of the encoder is to be transmitted via a memoryless binary symmetric channel. The authors' approach involves an iterative algorithm for the design of the quantizers (in the presence of channel errors) used for encoding the transform coefficients. This algorithm produces a set of locally optimum (in the mean-squared error sense) quantizers and the corresponding binary codeword assignment for the assumed transform coefficient statistics. To determine the optimum bit assignment among the transform coefficients, the authors have used an algorithm based on the steepest descent method, which, under certain convexity conditions on the performance of the channel-optimized quantizers, yields the optimal bit allocation. Simulation results for the performance of this locally optimum system over noisy channels have been obtained, and appropriate comparisons with a reference system designed for no channel errors have been made. It is shown that substantial performance improvements can be obtained by using this scheme. Furthermore, theoretically predicted results and rate distortion-theoretic bounds for an assumed two-dimensional image model are provided.<
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