Tree encoding of images in the presence of channel errors

Abstract

The performance and complexity of tree encoding of images in the presence of channel errors is considered. We demonstrate that a variation of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(M, L)</tex> algorithm yields performance close to the rate-distortion bound in the absence of channel errors for synthetic images modeled as two-dimensional autoregressive random fields. Trade-offs in optimizing the choice of tree search parameters are described, and experimental results on real-world images are presented. Simple tree search procedures are shown to provide signal-to-noise improvements in excess of 5 dB over conventional two-dimensional DPCM at the important rate of one bit/pixel; the effect is clear and striking to the eye. Channel error effects are treated by computer simulation and demonstrate signal-to-noise ratio improvement as high as 8 dB using tree encoding. Finally, a combined source-channel coding approach is described that exploits the significant trade-offs between source quantization accuracy and vulnerability to channel errors.