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   -> Volume 6, Issue 5

Preprint: Wavelet based image coding using morphology.
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Sergio Servetto (

PostPosted: Sat Apr 26, 1997 10:35 pm    
Subject: Preprint: Wavelet based image coding using morphology.
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#5 Preprint: Wavelet based image coding using morphology.

Image Coding based on a Morphological Representation of Wavelet Data.

Sergio D. Servetto, Kannan Ramchandran, and Michael T. Orchard.

Since their introduction as a tool for signal representation,
wavelets have become increasingly popular within the image coding
community, because of the potential gains they offer for the
construction of efficient image coding algorithms. Such potential
gains are due to the fact that wavelets provide a good tradeoff
between resolution in the space and frequency domains, a feature
which results in mapping typical space-domain image phenomena (such
as smooth regions and edges) into structured sets of coefficients in
the wavelet domain. However, to be able to make use of any
structure for improving coding performance, an algorithm requires a
statistical characterization of the joint distribution of wavelet
coefficients, capable of taking such structure into account. This
work presents both an experimental study of the statistics of
wavelet data, as well as the design of two different
morphology-based coding algorithms, that make use of these
statistics. A salient feature of the proposed method is that by a
simple change of quantizers, the same basic algorithm yields high
performance embedded or fixed rate coders. Another important
feature is that the shape information of morphological sets used in
this coder is encoded implicitly by the values of the wavelet
coefficients, thus avoiding the use of explicit (and rate expensive)
shape descriptors such as chain codes. These algorithms, while
achieving nearly the same objective performance of state-of-the-art
Zerotree based methods, are able to produce reconstructions of a
somewhat superior perceptual quality, due to a property of joint
compression and noise reduction they exhibit.

This paper was submitted last December to the IEEE Transactions on Image
Processing, and is currently under review. A copy can be obtained from:

Also, more information about this work (animations, source code, etc) are
available at the website

Sergio Servetto
PhD Candidate, Department of Computer Science
Graduate Research Assistant, Coordinated Science Lab. and Beckman Institute
University of Illinois at Urbana-Champaign.
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