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