Blind Multichannel Image Deconvolution and Optimum Sparse Approximations
Harikumar, G.
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https://hdl.handle.net/2142/81183
Description
Title
Blind Multichannel Image Deconvolution and Optimum Sparse Approximations
Author(s)
Harikumar, G.
Issue Date
1997
Doctoral Committee Chair(s)
Bresler, Yoram
Department of Study
Electrical 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
The second problem is one of computing maximally sparse elements of a convex, compact set. This problem arises in a wide range of engineering applications, including regularization of ill-posed problems, design of digital filters with few non-zero coefficients and the computation of sparse approximate solutions to inverse problems. Because the problem is N-P complete, there exists a need to develop heuristic techniques that work well for specific problems. Our contribution is the development of a new class of iterative algorithms for identifying sparse elements of the convex and compact set. We show that the algorithm has good convergence properties through a detailed theoretical analysis and demonstrate its performance on some examples.
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