title: Image denoising using nonsubsampled shearlet transform and twin support vector machines.
abstract: Denoising of images is one of the most basic tasks of image processing. It is a challenging work to design a edge/texture-preserving image denoising scheme. Nonsubsampled shearlet transform (NSST) is an effective multi-scale and multi-direction analysis method, it not only can exactly compute the shearlet coefficients based on a multiresolution analysis, but also can provide nearly optimal approximation for a piecewise smooth function. Based on NSST, a new edge/texture-preserving image denoising using twin support vector machines (TSVMs) is proposed in this paper. Firstly, the noisy image is decomposed into different subbands of frequency and orientation responses using the NSST. Secondly, the feature vector for a pixel in a noisy image is formed by the spatial geometric regularity in NSST domain, and the TSVMs model is obtained by training. Then the NSST detail coefficients are divided into information-related coefficients and noise-related ones by TSVMs training model. Finally, the detail subbands of NSST coefficients are denoised by using the adaptive threshold. Extensive experimental results demonstrate that our method can obtain better performances in terms of both subjective and objective evaluations than those state-of-the-art denoising techniques. Especially, the proposed method can preserve edges and textures very well while removing noise.
authors.affiliation: School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, PR China. Electronic address: yhy_65@126.com.
authors.forename: Hong-Ying
authors.initials: HY
authors.lastname: Yang
authors.affiliation: School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, PR China; Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology, Nanjing 210094, PR China. Electronic address: wxy37@126.com.
authors.forename: Xiang-Yang
authors.initials: XY
authors.lastname: Wang
authors.affiliation: School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, PR China.
authors.forename: Pan-Pan
authors.initials: PP
authors.lastname: Niu
authors.affiliation: School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, PR China.
authors.forename: Yang-Cheng
authors.initials: YC
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D016477:Artifacts; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D060388:Support Vector Machine
keywords: Adaptive denoising threshold; Image denoising; Nonsubsampled shearlet transform; Twin support vector machines