Two-Dimensional DPCM Image Coding Based on an Assumed Stochastic Image Model

Abstract
A new approach to the design of the feedback predictor in a two-dimensional (2-D) DPCM encoder is presented. This approach is based upon an assumed stochastic image model which exhibits the predominant and pronounced edge structure typical of real-world imagery and is in distinction from the conventional approach based upon 2-D autoregressive (AR) modeling assumptions. The performance of the resulting DPCM encoder is shown to offer significant performance advantages over existing DPCM design approaches at transmission rates of 2 bits/pixel or less. Furthermore, this new approach results in improved ability to cope with channel errors.

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