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 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.
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References
Buades, A., Coll, B., Morel, J.: A non-local algorithm for image denoising. In: IEEE Conference Computer Vision and Pattern Recognition, CVPR 2005, vol. 2, pp. 60–65 (2005)
Aharon, M., Elad, M., Bruckstein, A.: K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Sig. Process. 54(11), 4311–4322 (2006)
Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080–2095 (2007)
Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: 1998 IEEE International Conference on Computer Vision, Bombay, India, pp. 839–846 (1998)
Bennett, E.P., McMillan, L.: Video enhancement using per-pixel virtual exposures. In: ACM SIGGRAPH 2005 Papers, New York, NY, USA, pp. 845–852 (2005)
Danielyan, A., Foi, A., Katkovnik, V., Egiazarian, K.: Image and video super-resolution via spatially adaptive block matching filtering. In: Proceedings of International Workshop on Local and Non-Local Approximation in Image Processing (LNLA) (2008)
Leclercq, P., Morris, J.: Robustness to noise of stereo matching. In: Proceedings 12th International Conference on Image Analysis and Processing, pp. 606–611 (2003)
Malik, A.S., Choi, T.S., Nisar, H.: Depth Map and 3D Imaging Applications: Algorithms and Technologies, 1st edn. IGI Global, Hershey (2011)
Samani, A., Winkler, J., Niranjan, M.: Automatic face recognition using stereo images. In: 2006 IEEE International Conference on Speech and Signal Processing, vol. 5, p. V (2006)
Zhang, L., Vaddadi, S., Jin, H., Nayar, S.K.: Multiple view image denoising. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1542–1549 (2009)
Heo, Y.S., Lee, K.M., Lee, S.U.: Simultaneous depth reconstruction and restoration of noisy stereo images using non-local pixel distribution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)
Alkinani, M.H., El-Sakka, M.R.: Non-local means for stereo image denoising using structural similarity. In: Kamel, M., Campilho, A. (eds.) Image Analysis and Recognition. LNCS, vol. 9164, pp. 51–59. Springer, Switzerland (2015)
Narwaria, M., Lin, W.: SVD-based quality metric for image and video using machine learning. IEEE Trans. Syst. Man Cybern. Part B Cybern. 42(2), 347–364 (2012)
Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)
Acknowledgment
This 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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Alkinani, M.H., El-Sakka, M.R. (2016). Denoising Multi-view Images Using Non-local Means with Different Similarity Measures. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_12
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DOI: https://doi.org/10.1007/978-3-319-41501-7_12
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