Nonlinear Prediction in Image Coding with DPCM

Document Type

Article

Publication Date

1-1-1990

Abstract

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.

Identifier

0025471026 (Scopus)

Publication Title

Electronics Letters

External Full Text Location

https://doi.org/10.1049/el:19900873

ISSN

00135194

First Page

1357

Last Page

1359

Issue

17

Volume

26

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