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Article Navigation >  Journal of University of Electronic Science and Technology of China  > 2015  >  44(1): 84-90

LUO Xue-gang, Lü Jun-rui, WANG Hua-jun, YANG Qiang. Fast Nonlocal Means Image Denoising Algorithm Using Selective Calculation[J]. Journal of University of Electronic Science and Technology of China, 2015, 44(1): 84-90. doi: 10.3969/j.issn.1001-0548.2015.01.014
Citation: LUO Xue-gang, Lü Jun-rui, WANG Hua-jun, YANG Qiang. Fast Nonlocal Means Image Denoising Algorithm Using Selective Calculation[J]. Journal of University of Electronic Science and Technology of China, 2015, 44(1): 84-90. doi: 10.3969/j.issn.1001-0548.2015.01.014
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Fast Nonlocal Means Image Denoising Algorithm Using Selective Calculation

doi: 10.3969/j.issn.1001-0548.2015.01.014
  • 1.

    School of Mathematics and Computer Science,Panzhihua University Panzhihua Sichuan 617000;

  • 2.

    Key Lab of Earth Exploration & Information Techniques of Ministry of Education,Chengdu University of Technology Chengdu 610059

  • Received Date: 2013-09-16
  • Rev Recd Date: 2014-07-23
  • Publish Date: 2015-02-15
  • A fast nonlocal means (NLM) image denoising method with selective calculation is proposed to solve the problem that the computational cost of similarity weights is high. By using L2 Norm successive elimination, a large number of pixels of low similarity van be rejected through a small amount of additive operations on integral image, and the massive calculation on measuring similarity can be effectively reduced. According to spatial coherence in the image domain, an approach for adaptive search area based on patch geodesic distance is proposed. Experimental results demonstrate that the proposed method, compared with the state-of-the-art algorithms, can not only accelerate the nonlocal means algorithm, but also elevate the image quality.
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  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Fast Nonlocal Means Image Denoising Algorithm Using Selective Calculation

doi: 10.3969/j.issn.1001-0548.2015.01.014
  • 1. School of Mathematics and Computer Science,Panzhihua University Panzhihua Sichuan 617000;
  • 2. Key Lab of Earth Exploration & Information Techniques of Ministry of Education,Chengdu University of Technology Chengdu 610059
  • Received Date: 2013-09-16
  • Rev Recd Date: 2014-07-23
  • Publish Date: 2015-02-15

Abstract: A fast nonlocal means (NLM) image denoising method with selective calculation is proposed to solve the problem that the computational cost of similarity weights is high. By using L2 Norm successive elimination, a large number of pixels of low similarity van be rejected through a small amount of additive operations on integral image, and the massive calculation on measuring similarity can be effectively reduced. According to spatial coherence in the image domain, an approach for adaptive search area based on patch geodesic distance is proposed. Experimental results demonstrate that the proposed method, compared with the state-of-the-art algorithms, can not only accelerate the nonlocal means algorithm, but also elevate the image quality.

LUO Xue-gang, Lü Jun-rui, WANG Hua-jun, YANG Qiang. Fast Nonlocal Means Image Denoising Algorithm Using Selective Calculation[J]. Journal of University of Electronic Science and Technology of China, 2015, 44(1): 84-90. doi: 10.3969/j.issn.1001-0548.2015.01.014
Citation: LUO Xue-gang, Lü Jun-rui, WANG Hua-jun, YANG Qiang. Fast Nonlocal Means Image Denoising Algorithm Using Selective Calculation[J]. Journal of University of Electronic Science and Technology of China, 2015, 44(1): 84-90. doi: 10.3969/j.issn.1001-0548.2015.01.014
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