Please use this identifier to cite or link to this item:
Title: Tight frame methods for deconvolution
Keywords: deconvolution, denoising, framelets, quasi-affine system, Toeplitz matrix, unitary extension principle
Issue Date: 9-Feb-2006
Citation: CHAI ANWEI (2006-02-09). Tight frame methods for deconvolution. ScholarBank@NUS Repository.
Abstract: This thesis devotes to analyzing deconvolution algorithms using framelet approaches, which has appeared in framelet based high resolution image reconstruction methods. We first give a complete formulation of deconvolution in terms of multiresolution analysis and its approximation. This formulation converts deconvolution to problems of filling missing framelet coefficients which satisfy certain minimization properties. The missing framelet coefficients are recovered iteratively together with a built-in denoising scheme which prevent noises in data from blowing up while iterating. This approach has been proven to be efficient in solving various problems in high resolution image reconstructions. However, analysis of convergence as well as stability of algorithms and the optimal properties of solutions were absent in those works. This thesis is to establish the theoretical foundation of this framelet approach. In particular, proofs of convergence, analysis of the stability of the algorithms and a study of the minimization property of solutions are given.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Tight_Frame_Methods_for_Deconvolution-AnweiChai.pdf582.38 kBAdobe PDF



Page view(s)

checked on Mar 10, 2019


checked on Mar 10, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.