Volume 22, Issue 3
Multiplicative Noise Removal Based on Unbiased Box-Cox Transformation

Yu-Mei Huang, Hui-Yin Yan & Tieyong Zeng

Commun. Comput. Phys., 22 (2017), pp. 803-828.

Published online: 2017-09

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  • Abstract

Multiplicative noise removal is a challenging problem in image restoration. In this paper, by applying Box-Cox transformation, we convert the multiplicative noise removal problem into the additive noise removal problem and the block matching three dimensional (BM3D) method is applied to get the final recovered image. Indeed, BM3D is an effective method to remove additive Gaussian white noise in images. A maximum likelihood method is designed to determine the parameter in the Box-Cox transformation. We also present the unbiased inverse transform for the Box-Cox transformation which is important. Both theoretical analysis and experimental results illustrate clearly that the proposed method can remove multiplicative noise very well especially when multiplicative noise is heavy. The proposed method is superior to the existing methods for multiplicative noise removal in the literature.

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@Article{CiCP-22-803, author = {}, title = {Multiplicative Noise Removal Based on Unbiased Box-Cox Transformation}, journal = {Communications in Computational Physics}, year = {2017}, volume = {22}, number = {3}, pages = {803--828}, abstract = {

Multiplicative noise removal is a challenging problem in image restoration. In this paper, by applying Box-Cox transformation, we convert the multiplicative noise removal problem into the additive noise removal problem and the block matching three dimensional (BM3D) method is applied to get the final recovered image. Indeed, BM3D is an effective method to remove additive Gaussian white noise in images. A maximum likelihood method is designed to determine the parameter in the Box-Cox transformation. We also present the unbiased inverse transform for the Box-Cox transformation which is important. Both theoretical analysis and experimental results illustrate clearly that the proposed method can remove multiplicative noise very well especially when multiplicative noise is heavy. The proposed method is superior to the existing methods for multiplicative noise removal in the literature.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2016-0074}, url = {http://global-sci.org/intro/article_detail/cicp/9982.html} }
TY - JOUR T1 - Multiplicative Noise Removal Based on Unbiased Box-Cox Transformation JO - Communications in Computational Physics VL - 3 SP - 803 EP - 828 PY - 2017 DA - 2017/09 SN - 22 DO - http://doi.org/10.4208/cicp.OA-2016-0074 UR - https://global-sci.org/intro/article_detail/cicp/9982.html KW - AB -

Multiplicative noise removal is a challenging problem in image restoration. In this paper, by applying Box-Cox transformation, we convert the multiplicative noise removal problem into the additive noise removal problem and the block matching three dimensional (BM3D) method is applied to get the final recovered image. Indeed, BM3D is an effective method to remove additive Gaussian white noise in images. A maximum likelihood method is designed to determine the parameter in the Box-Cox transformation. We also present the unbiased inverse transform for the Box-Cox transformation which is important. Both theoretical analysis and experimental results illustrate clearly that the proposed method can remove multiplicative noise very well especially when multiplicative noise is heavy. The proposed method is superior to the existing methods for multiplicative noise removal in the literature.

Yu-Mei Huang, Hui-Yin Yan & Tieyong Zeng. (2020). Multiplicative Noise Removal Based on Unbiased Box-Cox Transformation. Communications in Computational Physics. 22 (3). 803-828. doi:10.4208/cicp.OA-2016-0074
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