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   -> Volume 6, Issue 1


Preprint: Image compression via a statistical model of wavelets
 
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Author Message
Eero Simoncelli (simoncel@math1.cims.nyu.edu)
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PostPosted: Fri Dec 20, 1996 2:37 am    
Subject: Preprint: Image compression via a statistical model of wavelets
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#2 Preprint: Image compression via a statistical model of wavelets

Dear Wavelet Digest readers,

I've just made available a preprint of our paper describing the joint
statistics of wavelet coefficients of natural images at adjacent
scales. This is an extension of the work in my previously posted
preprint (WD, 7/12/96, vol5, num5: "Noise Removal via Bayesian Wavelet
Coring").

TITLE: Progressive Wavelet Image Coding Based on a Conditional
Probability Model.

AUTHORS: Robert W. Buccigrossi and Eero P. Simoncelli

URL: http://www.cis.upenn.edu/~eero/publications.html

ABSTRACT: We present a wavelet image coder based on an explicit model
of the conditional statistical relationships between coefficients in
different subbands. In particular, we construct a parameterized model
for the conditional probability of a coefficient given coefficients at
a coarser scale. Subband coefficients are encoded one bitplane at a
time using a non-adaptive arithmetic encoder. The overall ordering of
bitplanes is determined by the ratio of their encoded variance to
compressed size. We show rate-distortion comparisons of the coder to
first and second-order theoretical entropy bounds and the EZW coder
(Shapiro, 1993). The coder is inherently embedded, and should prove
useful in applications requiring progressive transmission.

Comments/criticism welcomed!

Eero Simoncelli
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