Abstract
Non-Local Means (NLM) is a powerful but computationally expensive image denoising algorithm, which estimates a noiseless pixel as a weighted average across a large surrounding region whereby pixels centered at more similar patches are given higher weights. In this paper, we propose a method aimed at improving the computational efficiency of NLM by quick pre-selection of dissimilar patches thanks to a rapidly computable upper bound of the weighting function. Unlike previous approaches, our technique mathematically guarantees all highly correlated patches to be accounted for while discarding dissimilar ones, this providing not only faster speed but improved denoising too.
Chapter PDF
Similar content being viewed by others
References
Brox, T., Kleinschmid, O., Cremers, D.: Efficient nonlocal means for denoising of textural patterns. IEEE Trans. Image Processing 17(7), 1083–1092 (2008)
Buades, A., Coll, B., Morel, J.: A review of image denoising methods, with a new one. SIAM Multiscale Modeling and Simulation 4(2), 490–530 (2005)
Crow, F.: Summed-area tables for texture mapping. Computer Graphics 18(3), 207–212 (1984)
Danielyan, A., Katkovnik, V., Egiazarian, K.: Bm3d frames and variational image deblurring. IEEE Trans. Image Processing 21(4), 1715–1728 (2012)
Karnati, V., Uliyar, M., Dey, S.: Fast non-local algorithm for image denoising. In: Proc. Int. Conf. on Image Processing (ICIP) (2009)
Lewis, J.: Fast template matching. Vision Interface, pp. 120–123 (1995)
Liu, Y., Wang, J., Chen, X., Guo, Y., Peng, Q.: A robust and fast non-local means algorithm for image denoising. J. Computer Science and Technology 23(2), 270–279 (2008)
Mahmoudi, M., Sapiro, G.: Fast image and video denoising via nonlocal means of similar neighborhoods. IEEE Signal Processing Letters 12(12), 839–842 (2005)
McDonnell, M.: Box-filtering techniques. Computer Graphics and Image Processing 17(1), 65–70 (1981)
Ouyang, W., Tombari, F., Mattoccia, S., Di Stefano, L., Cham, W.K.: Performance evaluation of full search equivalent pattern matching algorithms. Trans. Pattern Analysis and Machine Intelligence (PAMI) 34(1), 127–143 (2012)
Tasdizen, T.: Principal neighborhood dictionaries for nonlocal means image denoising. IEEE Trans. Image Processing 18(12), 2649–2660 (2009)
Tombari, F., Mattoccia, S., Di Stefano, L.: Full search-equivalent pattern matching with incremental dissimilarity approximations. Trans. Pattern Analysis and Machine Intelligence (PAMI) 31(1), 129–141 (2009)
Vignesh, R., Oh, B., Kuo, C.: Fast non-local means (nlm) computation with probabilistic early termination. IEEE Signal Processing Letters 17(3), 277–280 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Tombari, F., Di Stefano, L. (2015). Bounded Non-Local Means for Fast and Effective Image Denoising. In: Murino, V., Puppo, E. (eds) Image Analysis and Processing — ICIAP 2015. ICIAP 2015. Lecture Notes in Computer Science(), vol 9280. Springer, Cham. https://doi.org/10.1007/978-3-319-23234-8_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-23234-8_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23233-1
Online ISBN: 978-3-319-23234-8
eBook Packages: Computer ScienceComputer Science (R0)