Pattern matching image compression

Abstract

We propose a non-transform image compression scheme based on approximate pattern matching, that we name pattern matching linage compression (PMIC). The main idea behind it is a lossy extension of the Lempel-Ziv data compression scheme in which one searches for the longest prefix of an uncompressed image that approximately occurs in the already processed image. We consider both the Hamming distance and the square error distortion. The theoretical basis for such a scheme was laid out by Luczak and Szpankowski [1994, 1995]. A straightforward implementation of the basic scheme described in Luczak and Szpankowski on real images (structured data) seems not to be attractive from a practical point of view. The main algorithm is therefore enhanced with several new features 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 D, and so forth. These enhancements are crucial to the overall quality of our scheme.