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Title:Representation and coding of images using wavelets
Author(s):Xiong, Zixiang
Doctoral Committee Chair(s):Ramchandran, Kannan
Department / Program:Electrical and Computer Engineering
Discipline:Electrical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Engineering, Electronics and Electrical
Abstract:Recently, there have been intense research activities in the theory of wavelets, driven by its application in a wide variety of areas, especially in image processing. This dissertation presents a body of work addressing the application aspects of wavelets in representation and coding of images.
We first introduce a novel space-frequency quantization (SFQ) scheme for wavelet image coding, which jointly optimizes scalar quantization and zerotree quantization using a rate-distortion optimization framework. The SFQ scheme can be viewed as a variant of Shapiro's embedded zerotree image coder (1) with impressive coding gain. We then extend SFQ from wavelet to wavelet packet (possibly space-varying) decompositions, achieving coding performance that is the best in the published literature.
We then examine the question of how to choose a space-varying wavelet packet tree representation that minimizes some additive cost function for an image. The idea is that for a practical cost function, some tree structures will perform better than others. We build new libraries of tree-structured bases for image representation with space-varying wavelet packets and devise fast algorithms for finding the best basis from the libraries. Using these algorithms to select the best tree-structured representation with a rate-distortion cost function gives very efficient adaptive compression schemes that are competitive with the best training-based schemes.
Issue Date:1996
Type:Text
Language:English
URI:http://hdl.handle.net/2142/20956
ISBN:9780591199703
Rights Information:Copyright 1996 Xiong, Zixiang
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI9712488
OCLC Identifier:(UMI)AAI9712488


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