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An edge-preserving adaptive image denoising

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Abstract

Based on nonsubsampled shearlet transform (NSST) and fuzzy support vector machines (FSVMs), we present a new denoising approach that can effectively suppress noise from an image while keeping its features intact. The noisy image is firstly decomposed into different subbands of frequency and orientation responses using NSST. The NSST detail coefficients are then divided into edge/texture-related coefficients and noise-related ones by FSVMs classifier. And finally the detail subbands of NSST coefficients are denoised by using the adaptive Bayesian threshold. Extensive experimental results demonstrate that our approach is competitive relative to many state-of-the-art denoising techniques. Especially, the proposed method can preserve edges very well while removing noise.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant No. 61472171 & 61272416, the Open Project Program of Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology) under Grant No. 30920130122006, the Open Foundation of Zhejiang Key Laboratory for Signal Processing under Grant No. ZJKL_4_SP-OP2013-01, the Open Foundation of Provincial Key Laboratory for Computer Information Processing Technology (Soochow University) under Grant No. KJS1325, the Open Project Program of the State Key Lab of CAD&CG (Grant No. A1425), Zhejiang University, and Liaoning Research Project for Institutions of Higher Education of China under Grant No. L2013407.

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Authors and Affiliations

  1. School of Computer and Information Technology, Liaoning Normal University, Dalian, 116029, People’s Republic of China

    Xiang-Yang Wang, Yang-Cheng Liu, Na Zhang, Chang-Jian Wu & Hong-Ying Yang

  2. Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Soochow, 215006, People’s Republic of China

    Xiang-Yang Wang

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  1. Xiang-Yang Wang
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  2. Yang-Cheng Liu
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  3. Na Zhang
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  4. Chang-Jian Wu
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  5. Hong-Ying Yang
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Correspondence to Xiang-Yang Wang or Hong-Ying Yang.

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Wang, XY., Liu, YC., Zhang, N. et al. An edge-preserving adaptive image denoising. Multimed Tools Appl 74, 11703–11720 (2015). https://doi.org/10.1007/s11042-014-2258-x

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  • DOI: https://doi.org/10.1007/s11042-014-2258-x

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