@Article{CiCP-22-803,
author = {Yu-Mei Huang, Hui-Yin Yan and Tieyong Zeng},
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 = {<p style="text-align: justify;">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.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.OA-2016-0074},
url = {http://global-sci.org/intro/article_detail/cicp/9982.html}
}