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PATTERN MATCHING IMAGE COMPRESSION
WITH PREDICATION LOOP:
Preliminary Experimental Results

Denis Arnaud Wojciech Szpankowski[*]
ENST Department of Computer Science
46 Rue Barrault Purdue University
75013 Paris W. Lafayette, IN 47907
France U.S.A.
darnaud@email.enst.fr spa@cs.purdue.edu







Abstract

Recently, a novel image compression technique based on pattern matching was proposed, namely Pattern Matching Image Compression (PMIC). Basically, it is a lossy extension of the well known Lempel-Ziv scheme. It was proved that such an extension leads to a suboptimal compression, and that the compression ratio can as low as the so called Rényi entropy. Success of PMIC crucially depends on several enhancements such as searching for reverse approximate matching, recognizing substrings in images that are additively shifted versions of each other, introducing a variable and adaptive maximum distortion level, and so forth. In this paper, we introduce another enhancement, namely, predictive coding. More precisely, we implement Differential Predictive Code Modulation (DPCM) within PMIC scheme. We report here some preliminary experimental results which show that PMIC enhanced by DPCM can improve compression ratio for good quality images as well as speed of compression for PMIC.

A PDF version is also available here.



 
next up previous
Next: 1 Introduction
Denis Arnaud
11/19/1997