Title :
Fast Non-Local algorithm for image denoising
Author :
Karnati, Venkateswarlu ; Uliyar, Mithun ; Dey, Sumit
Author_Institution :
Aricent, Bangalore, India
Abstract :
In this paper, improvements to non-local means (NLM) image denoising method is proposed to reduce the computational complexity. In the original NLM algorithm, neighborhood weightages are computed using the window similarity technique. The proposed technique replaces the window similarity by a modified multi-resolution based approach with much fewer comparisons rather than all pixels comparison. This approach also uses the concept of filtering out non-similar neighborhood pixels based on fixed sized window gray mean values. Further, mean values of the variable sized windows in the image are computed efficiently using summed image (SI) concept, which requires only 3 additions. The proposed approach is nearly 80 times faster than original Baudes NLM algorithm with close subjective and objective quality measurements.
Keywords :
image denoising; image resolution; computational complexity; fixed sized window gray mean values; image denoising; modified multiresolution based approach; nonlocal means image denoising method; objective quality measurements; summed image concept; window similarity technique; Biomedical imaging; Computational complexity; Filtering; Filters; Image denoising; Image edge detection; Image resolution; Image restoration; Noise reduction; Pixel; Image Denoising; Multi Resolution; Non Local Mean; Summed Image;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414044