LZ-based adaptive compression for images

Authors:
Bruno Carpentieri
Affiliations:
-
Venue:
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
Year:
2011

Citing 4
Cited 0

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Abstract

Textual substitution methods, often called dictionary methods, or Lempel-Ziv methods, are one-dimensional compression methods that maintain a constantly changing dictionary of strings to adaptively compress a stream of characters by replacing common sub strings with indices (pointers) into the dictionary. We review some of our recent work on LZ-based, single pass, adaptive algorithms for the compression of digital images and we experimentally analyze the behavior of this algorithm with respect to the local dictionary size.