Error Modeling for Hierarchical Lossless Image Compression
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Issue Date
1992Author
Howard, Paul G.
Vitter, Jeffrey Scott
Publisher
IEEE
Type
Article
Article Version
Scholarly/refereed, author accepted manuscript
Metadata
Show full item recordAbstract
We present a new method for error modeling applicable to the MLP algorithm
for hierarchical lossless image compression. This method, based on a concept
called the variability index, provides accurate models for pixel prediction errors
without requiring explicit transmission of the models. We also use the vari-
ability index to show that prediction errors do not always follow the Laplace
distribution, as is commonly assumed; replacing the Laplace distribution with a
more general symmetric exponential distribution further improves compression.
We describe a new compression measurement called compression gain, and we
give experimental results showing that the MLP method using the variability
index technique for error modeling gives signi cantly more compression gain
than other methods in the literature.
Description
(c) 1992 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
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Citation
P. G. Howard and J. S. Vitter. “Error Modeling for Hierarchical Lossless Image Compression,” Proceedings of the 1992 IEEE Data Compression Conference (DCC ’92), Snowbird, UT, March 1992, 269–278. http://dx.doi.org/10.1109/DCC.1992.227454
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