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 Non-local Means algorithm for denoising collected patches from the searching windows. Experimental results show that our algorithm outperforms the original Non-local Means and our previous method Stereo images denoising using Non-local Means with Structural SIMilarity (S-SSIM), and it helps to estimate more accurate disparity maps at various noise levels.