Fuzzy Weighted Non-Local Means method (FWNLM)

Abstract

In this paper, we propose a fuzzy weighted non-local means filter for the removal of random-valued impulse noise. We introduce a new fuzzy weighting function, which can shut off the impulsive weight effectively, to the non-local means. According to the new weighting function, the more a pixel is corrupted, the less it is exploited to reconstruct image information. Experiments show that the performances of the new filter are surprisingly satisfactory in terms of both visual quality and quantitative measurement. Moreover, our filter also can be used to remove mixed Gaussian and random-valued impulse noise.

Source Code Article
Disclaimer: This code is provided as-is and was implemented by the developers of this project. Users are advised to use it at their own risk. The authors are not liable for any damages or unintended consequences resulting from its use.

Reference

J. Wu, C. Tang, Random-valued impulse noise removal using fuzzy weighted non-local means, Signal, Image and Video Processing 8 (2014) 349–355. 


                
    @Article{Wu-Tang-2014,
    author  = {Jian Wu and Chen Tang},
    title   = {Random-valued impulse noise removal using fuzzy weighted non-local means},
    pages   = {349–355},
    volume  = {8},
    journal = {Signal, Image and Video Processing},
    year    = {2014},
    }