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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 = {Yumei Huang, Michael Ng and Tieyong Zeng}, 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 AU - Yumei Huang, Michael Ng & Tieyong Zeng 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 and Tieyong Zeng. (2013). 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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