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Gaussian principle components for nonlocal means image denoising

  • Published:
Journal of Electronics (China)

Abstract

NonLocal Means (NLM), taking fully advantage of image redundancy, has been proved to be very effective in noise removal. However, high computational load limits its wide application. Based on Principle Component Analysis (PCA), Principle Neighborhood Dictionary (PND) was proposed to reduce the computational load of NLM. Nevertheless, as the principle components in PND method are computed directly from noisy image neighborhoods, they are prone to be inaccurate due to the presence of noise. In this paper, an improved scheme for image denoising is proposed. This scheme is based on PND and uses preprocessing via Gaussian filter to eliminate the influence of noise. PCA is then used to project those filtered image neighborhood vectors onto a lower-dimensional space. With the preprocessing process, the principle components computed are more accurate resulting in an improved denoising performance. A comparison with some NLM based and state-of-art denoising methods shows that the proposed method performs well in terms of Peak Signal to Noise Ratio (PSNR) as well as image visual fidelity. The experimental results demonstrate that our method outperforms existing methods both subjectively and objectively.

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Authors and Affiliations

  1. Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China, Xidian University, Xi’an, 710071, China

    Xiangping Li, Xiaotian Wang & Guangming Shi

  2. Xidian University, Mailbox 77, 2 South Taibai Road, Xi’an, 710071, China

    Xiangping Li

Authors
  1. Xiangping Li
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  2. Xiaotian Wang
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  3. Guangming Shi
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Corresponding author

Correspondence to Xiangping Li.

Additional information

Supported by the National Natural Science Foundation of China (No. 60776795, 60736043, 60902031, and 60805012), the Research Fund for the Doctoral Program of Higher Education of China (No. 200807010004, 20070701023), the Fundamental Research Funds for the Central Universities of China (No. JY10000902028).

Communication author: Li Xiangping, born in 1987, female, Master Degree.

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Li, X., Wang, X. & Shi, G. Gaussian principle components for nonlocal means image denoising. J. Electron.(China) 28, 539–547 (2011). https://doi.org/10.1007/s11767-012-0723-0

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  • DOI: https://doi.org/10.1007/s11767-012-0723-0

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