NONLINEAR PREDICTION IN IMAGE-CODING WITH DPCM

In contrast to the traditional linear differential pulse code modulation (DPCM) design for the encoding of images, a new, nonlinear, neural network-based, DPCM technique has been devised. The predictor is designed by supervised train ing, based on a typical sequence of pixel values in an image. A function link neural network architecture has been used to design the predictor for one dimensional (1-D) DPCM. Com puter simulation experiments in still image coding have shown that the resulting encoders work very well. At a trans mission rate of 1 bit/pixel, for the image LENA, the 1-D neural network DPCM provides a 4-2 dB improvement in SNR over the standard linear DPCM system. © 1990, The Institution of Electrical Engineers. All rights reserved.