Non-Local Means Filters for Full Polarimetric Synthetic Aperture Radar Images with Stochastic Distances
Luis Gomez, Jie Wu, Alejandro C. Frery
published
2022-04-25
reference
Luis Gomez, Jie Wu, and Alejandro C. Frery, Non-Local Means Filters for Full Polarimetric Synthetic Aperture Radar Images with Stochastic Distances, Image Processing On Line, 12 (2022), pp. 142–172. https://doi.org/10.5201/ipol.2022.346

Communicated by Thibaud Ehret
Demo edited by Thibaud Ehret

Abstract

In this paper, we present a Non-Local Means filtering method for PolSAR (Polarimetric Synthetic Aperture Radar) imagery. We adopted three stochastic distances to measure the similarity of samples. We obtain p-values using the asymptotic distribution of test statistics based on these distances. Then we use this similarity evidence as input for a smooth activating function that yields the weights of local convolution matrices. Non-local filters are computationally demanding, so we provide an efficient implementation that allows us to experiment with different settings and find optimal parameters.

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