Fast implementation of two-level compression method using QM-coder

We deal with bi-level image compression. Modern methods consider the bi-level image as a high order Markovian source, and by exploiting this characteristic, can attain better performance. At a first glance, the increasing of the order of the Markovian model in the modelling process should yield a hi...

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Bibliographic Details
Published in:DCC (Los Alamitos, Calif.) p. 459
Main Authors: Nguyen-Phi, K., Weinrichter, H.
Format: Conference Proceeding Journal Article
Language:English
Published: IEEE 1997
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ISBN:9780818677618, 0818677619
ISSN:1068-0314
Online Access:Get full text
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Summary:We deal with bi-level image compression. Modern methods consider the bi-level image as a high order Markovian source, and by exploiting this characteristic, can attain better performance. At a first glance, the increasing of the order of the Markovian model in the modelling process should yield a higher compression ratio, but in fact, it is not true. A higher order model needs a longer time to learn (adaptively) the statistical characteristic of the source. If the source sequence, or the bi-level image in this case, is not long enough, then we do not have a stable model. One simple way to solve this problem is the two-level method. We consider the implementation aspects of this method. Instead of using the general arithmetic coder, an obvious alternative is using the QM-coder, thus reducing the memory used and increasing the execution speed. We discuss some possible heuristics to increase the performance. Experimental results obtained with the ITU-T test images are given.
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ISBN:9780818677618
0818677619
ISSN:1068-0314
DOI:10.1109/DCC.1997.582123