DocumentCode
2456009
Title
Power Iteration Denoising
Author
Gomo, Panganai ; Spann, Mike
Author_Institution
EECE, Univ. of Birmingham, Birmingham, UK
fYear
2010
fDate
12-14 Dec. 2010
Firstpage
846
Lastpage
850
Abstract
We present a simple method for image denoising called power iteration denoising (PID). PID finds a low dimensional embedding of the image data using a truncated power iteration on a normalized pair-wise similarity matrix generated from the image. This embedding turns out to be an effective denoising algorithm outperforming the widely used non-local means algorithm. We apply this method to the denoising of noisy digital camera images producing visually pleasing results.
Keywords
cameras; image denoising; denoising algorithm; image data; image denoising; low dimensional embedding; noisy digital camera images; nonlocal means algorithm; normalized pairwise similarity matrix; power iteration denoising; truncated power iteration; Clustering algorithms; Image denoising; Laplace equations; Noise measurement; Noise reduction; PSNR; Pixel; harmonic functions; non-local means; power iteration; semi-supervised machine learning; spectral clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
Conference_Location
Washington, DC
Print_ISBN
978-1-4244-9211-4
Type
conf
DOI
10.1109/ICMLA.2010.131
Filename
5708954
Link To Document