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Denoising is a key step in the processing of medical images. It aims at improving both the interpretability and visual aspect of the images. Yet, designing a robust and efficient denoising tool remains an unsolved challenge and a specific issue concerns the noise model. Many filters typically assume that noise is additive and Gaussian, with uniform variance. In contrast, noise in medical images often...
Edge-preserving filters such as local M-smoothers or bilateral filtering are usually designed for Gaussian noise. This paper investigates how these filters can be adapted in order to efficiently deal with Poissonian noise. In addition, the issue of photometry invariance is addressed by changing the way filter coefficients are normalized. The proposed normalization is additive, instead of being multiplicative,...
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