Non-local Means for Stereo Image Denoising Using Structural Similarity

  • Monagi H. Alkinani
  • Mahmoud R. El-SakkaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9164)


We present a novel stereo image denoising algorithm. Our algorithm takes as an input a pair of noisy images of an object captured form two different directions. We use the structural similarity index as a similarity metric for identifying locations of similar patches in the input images. We adapt the Non-Local Means algorithm for denoising collected patches from the input images. We validate our algorithm on various stereo images at various noise levels. Experimental results show that the denoising performance of our algorithm is better than the original Non-Local Means and Stereo-MSE methods at low noise level \(\left( \sigma \leqslant 20\right) \).


Non-local means Patch-based image filtering Stereo imaging Structural similarity index Additive noise reduction  Disparity map 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Computer Science DepartmentUniversity of Western OntarioLondonCanada

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