Denoising Multiview Images Using Nonlocal Means

Authors: Monagi H Alkinani Mahmoud R ElSakka

Publish Date: 2016/7/13

Volume: , Issue: , Pages: 101-109

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Abstract

We present a stereo image denoising algorithm Our algorithm takes as an input a pair of noisy images of an object captured from two different directions stereo images We use either Maximum Difference or Singular Value Decomposition similarity metrics for identifying locations of similar searching windows in the input images We adapt the Nonlocal Means algorithm for denoising collected patches from the searching windows Experimental results show that our algorithm outperforms the original Nonlocal Means and our previous method Stereo images denoising using Nonlocal Means with Structural SIMilarity SSSIM and it helps to estimate more accurate disparity maps at various noise levelsThis research is partially funded by the Natural Sciences and Engineering Research Council of Canada NSERC This support is greatly appreciated This research is also partially funded by the Cultural Bureau of Saudi Arabia in Canada This support is greatly appreciated

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