Abstract
We present a method for improving a non-local means (NLM) operator by computing its low-rank approximation. The low-rank operator is constructed by applying a filter to the spectrum of the original NLM operator. This results in an operator, which is less sensitive to noise while preserving important properties of the original operator. The method is efficiently implemented based on Chebyshev polynomials and is demonstrated on the application of natural images denoising. For this application, we provide a comparison of our method with other denoising methods.
Original language | English |
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Article number | 7384488 |
Pages (from-to) | 1340-1353 |
Number of pages | 14 |
Journal | IEEE Transactions on Image Processing |
Volume | 25 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2016 |
Bibliographical note
Publisher Copyright:© 1992-2012 IEEE.
Keywords
- Chebyshev polynomials
- Denoising
- Non-Local Means operator