Multiplicative Noise Removal Based on Unbiased Box-Cox Transformation. (6th July 2017)

• Record Type: Journal Article
• Authors: Huang, Yu-Mei; Yan, Hui-Yin; Zeng, Tieyong
• Is Part Of: Communications in computational physics. Volume 22:Number 3(2017:Sep.)
• Page Start: 803
• Page End: 828
• Publication Date: 2017-07-06
• Subjects: 62E17, -- 62F10, -- 65H05, -- 68U10; Multiplicative noise removal, -- Box-Cox transformation, -- maximum likelihood estimation, -- block-matching three dimensional method (BM3D); Mathematical physics -- Data processing -- Periodicals; Physics -- Data processing -- Periodicals; 530.150285
• DOI: 10.4208/cicp.OA-2016-0074
• Languages: English
• ISSNs: 1815-2406

Abstract

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.