Fast Non-Local Mean Filter Algorithm Based on Recursive Calculation of Similarity Weights
- Authors: Karnaukhov V.N.1, Mozerov M.G.1
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Affiliations:
- Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences
- Issue: Vol 63, No 12 (2018)
- Pages: 1475-1477
- Section: Mathematical Models and Computational Methods
- URL: https://journals.rcsi.science/1064-2269/article/view/199349
- DOI: https://doi.org/10.1134/S1064226918120070
- ID: 199349
Cite item
Abstract
Abstract—A theoretically derived technique for acceleration of the original non-local means image denoising algorithm based on calculation of recursive patch similarity weights is proposed. A significant amount of computation in the non-local means scheme is dedicated to estimation of the patch similarity between pixel neighborhoods. The proposed recursive weights calculation scheme adopts the classic recursive mean calculation scheme for a multidimensional shift-vector in order to lower the computational complexity of the original non-local means method, thus speeding up this algorithm more than tenfold. Note that the output of the proposed algorithm is exactly the same as that of the original non-local means method. Hence this algorithm belongs to the class of true fast algorithms, unlike methods approaching to a certain degree the resul of the original algorithm.
About the authors
V. N. Karnaukhov
Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences
Author for correspondence.
Email: vnk@iitp.ru
Russian Federation, Moscow, 127051
M. G. Mozerov
Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences
Email: vnk@iitp.ru
Russian Federation, Moscow, 127051