Feature-Based Texture Synthesis and Hierarchical Tensor Approximation
Wu, Qing
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Permalink
https://hdl.handle.net/2142/81806
Description
Title
Feature-Based Texture Synthesis and Hierarchical Tensor Approximation
Author(s)
Wu, Qing
Issue Date
2007
Doctoral Committee Chair(s)
Yu, Yizhou
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
Finally, we propose to apply multilinear models to wavelet domain to reduce overhead. High-frequency wavelet sub-bands are subdivided into small blocks most of which get pruned. The blocks are usually correlated especially when properly classified. Different channels and sub-bands may exhibit strong redundancy as well. We reorganize the subdivided blocks into small tensors, classify the unpruned ones and approximate each cluster as a tensor ensemble. Experiments on images and medical volume data indicate that this approach achieves better approximation quality than wavelet (packet) transforms and hybrid linear models.
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