• DocumentCode
    3543899
  • Title

    Adaptive nonlocal means algorithm for image denoising

  • Author

    Thaipanich, Tanaphol ; Oh, Byung Tae ; Wu, Ping-Hao ; Kuo, C. C Jay

  • Author_Institution
    Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2010
  • fDate
    9-13 Jan. 2010
  • Firstpage
    417
  • Lastpage
    418
  • Abstract
    An adaptive image denoising technique based on the nonlocal means (NL-means) algorithm is investigated in this research. The proposed method first employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique for robust block classification in noisy images. Then, the local window is adaptively adjusted to match the local property of a block. Finally, a rotated block matching algorithm is adopted for better similarity matching. Experiment results are given to demonstrate the superior denoising performance of the proposed adaptive NL-means (ANL-means) denoising technique.
  • Keywords
    image denoising; singular value decomposition; K-means clustering; adaptive nonlocal means algorithm; image denoising; robust block classification; rotated block matching algorithm; singular value decomposition; Clustering algorithms; Eigenvalues and eigenfunctions; Hydrogen; Image denoising; Noise cancellation; Noise reduction; Pixel; Robustness; Singular value decomposition; Wiener filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics (ICCE), 2010 Digest of Technical Papers International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4244-4314-7
  • Electronic_ISBN
    978-1-4244-4316-1
  • Type

    conf

  • DOI
    10.1109/ICCE.2010.5418875
  • Filename
    5418875