Automatic Robust NL-means denoising filter for additive and multiplicative noise
Most denoising methods require that some smoothing parameters be set manually to optimize their performance. Among these methods, a new filter based on nonlocal weighting (NL-means filter) has been shown to have a very attractive denoising capacity. In this paper, we propose fixing the smoothing parameter of this filter automatically. The smoothing parameter corresponds to the bandwidth h of a local constant regression. We use the Cp statistic embedded in Newton's method to optimize h in a point-wise fashion. This statistic also has the advantage of being a reliable measure of the quality of the denoising process for each pixel. In addition, we introduce a robust regression in the NL-means filter designed to greatly reduce the blur yielded by the weighting. Finally, we show how the automatic denoising model can be extended to images degraded by multiplicative noise.
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04732320
Cite As
Vincent Dore (2024). Automatic Robust NL-means denoising filter for additive and multiplicative noise (https://www.mathworks.com/matlabcentral/fileexchange/32041-automatic-robust-nl-means-denoising-filter-for-additive-and-multiplicative-noise), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Image Filtering >
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1.0.0.0 |