Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.acha.2011.09.006
Title: Image deconvolution using a characterization of sharp images in wavelet domain
Authors: Ji, H. 
Li, J.
Shen, Z. 
Wang, K.
Keywords: Image deconvolution
Wavelet tight frame
Issue Date: Mar-2012
Citation: Ji, H., Li, J., Shen, Z., Wang, K. (2012-03). Image deconvolution using a characterization of sharp images in wavelet domain. Applied and Computational Harmonic Analysis 32 (2) : 295-304. ScholarBank@NUS Repository. https://doi.org/10.1016/j.acha.2011.09.006
Abstract: Image deconvolution is a challenging ill-posed problem when only partial information of the blur kernel is available. Certain regularization on sharp images has to be imposed to constrain the estimation of true images during the blind deconvolution process. Based on the observation that an image of sharp edges tends to minimize the ratio between the l 1 norm and the l 2 norm of its wavelet frame coefficients, we propose a new characterization of sharp images for image deconvolution. A two-stage method is then developed to solve semi-blind image deconvolution problems. The proposed method is fast, easy to implement and does not require rigorous parameter tune-up. Such a regularization can also be applied to solve non-blind image deconvolution problems and the resulting algorithm achieves good performance without rigorous parameter tune-up. © 2011 Elsevier Inc. All rights reserved.
Source Title: Applied and Computational Harmonic Analysis
URI: http://scholarbank.nus.edu.sg/handle/10635/103395
ISSN: 10635203
DOI: 10.1016/j.acha.2011.09.006
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