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We study the problem of memory-efficient scalable image compression and investigate some tradeoffs in the complexity versus coding efficiency space. The focus is on a low-complexity algorithm centered around the use of sub-bit-planes, scan-causal modeling, and a simplified arithmetic coder. This algorithm approaches the lowest possible memory usage for scalable wavelet-based image compression and demonstrates that the generation of a scalable bit-stream is not incompatible with a low-memory architecture.
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Erik Ordentlich
Yahoo (United States)
David Taubman
UNSW Sydney
M.J. Weinberger
Stanford University
University of Arizona
UNSW Sydney
Hewlett-Packard (United States)
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Ordentlich et al. (Fri,) studied this question.
synapsesocial.com/papers/6a20a30caa8e57945c6d96c4 — DOI: https://doi.org/10.1109/dcc.1999.755671
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