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
Link To Document :
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