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Volume 13, Issue 4
The Convex Relaxation Method on Deconvolution Model with Multiplicative Noise

Yumei Huang, Michael Ng & Tieyong Zeng

DOI: 10.4208/cicp.310811.090312a

Commun. Comput. Phys., 13 (2013), pp. 1066-1092.

Published online: 2013-08

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  • Abstract

In this paper, we consider variational approaches to handle the multiplicative noise removal and deblurring problem. Based on rather reasonable physical blurring-noisy assumptions, we derive a new variational model for this issue. After the study of the basic properties, we propose to approximate it by a convex relaxation model which is a balance between the previous non-convex model and a convex model. The relaxed model is solved by an alternating minimization approach. Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed method.

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@Article{CiCP-13-1066, author = {}, title = {The Convex Relaxation Method on Deconvolution Model with Multiplicative Noise}, journal = {Communications in Computational Physics}, year = {2013}, volume = {13}, number = {4}, pages = {1066--1092}, abstract = {

In this paper, we consider variational approaches to handle the multiplicative noise removal and deblurring problem. Based on rather reasonable physical blurring-noisy assumptions, we derive a new variational model for this issue. After the study of the basic properties, we propose to approximate it by a convex relaxation model which is a balance between the previous non-convex model and a convex model. The relaxed model is solved by an alternating minimization approach. Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed method.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.310811.090312a}, url = {http://global-sci.org/intro/article_detail/cicp/7264.html} }
TY - JOUR T1 - The Convex Relaxation Method on Deconvolution Model with Multiplicative Noise JO - Communications in Computational Physics VL - 4 SP - 1066 EP - 1092 PY - 2013 DA - 2013/08 SN - 13 DO - http://doi.org/10.4208/cicp.310811.090312a UR - https://global-sci.org/intro/article_detail/cicp/7264.html KW - AB -

In this paper, we consider variational approaches to handle the multiplicative noise removal and deblurring problem. Based on rather reasonable physical blurring-noisy assumptions, we derive a new variational model for this issue. After the study of the basic properties, we propose to approximate it by a convex relaxation model which is a balance between the previous non-convex model and a convex model. The relaxed model is solved by an alternating minimization approach. Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed method.

Yumei Huang, Michael Ng & Tieyong Zeng. (2020). The Convex Relaxation Method on Deconvolution Model with Multiplicative Noise. Communications in Computational Physics. 13 (4). 1066-1092. doi:10.4208/cicp.310811.090312a
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