title: Improved Rotating Kernel Transformation Based Contourlet Domain Image Denoising Framework.
abstract: A contourlet domain image denoising framework based on a novel Improved Rotating Kernel Transformation is proposed, where the difference of subbands in contourlet domain is taken into account. In detail: (1). A novel Improved Rotating Kernel Transformation (IRKT) is proposed to calculate the direction statistic of the image; The validity of the IRKT is verified by the corresponding extracted edge information comparing with the state-of-the-art edge detection algorithm. (2). The direction statistic represents the difference between subbands and is introduced to the threshold function based contourlet domain denoising approaches in the form of weights to get the novel framework. The proposed framework is utilized to improve the contourlet soft-thresholding (CTSoft) and contourlet bivariate-thresholding (CTB) algorithms. The denoising results on the conventional testing images and the Optical Coherence Tomography (OCT) medical images show that the proposed methods improve the existing contourlet based thresholding denoising algorithm, especially for the medical images.
authors.affiliation: Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, 443002, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Guo
authors.affiliation: Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, 443002, China.
authors.forename: Fangmin
authors.initials: F
authors.lastname: Dong
authors.affiliation: Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, 443002, China; Collaborative Innovation Center for Geo-Hazards and Eco-Environment in Three Gorges Area, China Three Gorges University, Yichang, 443002, China.
authors.forename: Shuifa
authors.initials: S
authors.lastname: Sun
authors.affiliation: Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, 443002, China.
authors.forename: Xuhong
authors.initials: X
authors.lastname: Ren
authors.affiliation: Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, 443002, China.
authors.forename: Shiyu
authors.initials: S
authors.lastname: Feng
authors.affiliation: Department of Bioengineering, Clemson University, Clemson, SC, 29634, USA.
authors.forename: Bruce Zhi
authors.initials: BZ
authors.lastname: Gao
keywords: Contourlet transform; Direction statistic; Image denoising; Improved Rotating Kernel Transformation