Representation and coding of images using wavelets
Xiong, Zixiang
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https://hdl.handle.net/2142/20956
Description
Title
Representation and coding of images using wavelets
Author(s)
Xiong, Zixiang
Issue Date
1996
Doctoral Committee Chair(s)
Ramchandran, Kannan
Department of Study
Electrical and Computer Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
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.
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