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arXiv · 1001.5447

Locally adaptive image denoising by a statistical multiresolution criterion

Thomas Hotz·Philipp Marnitz·Rahel Stichtenoth·Laurie Davies·Zakhar Kabluchko·Axel Munk
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Abstract

We demonstrate how one can choose the smoothing parameter in image denoising by a statistical multiresolution criterion, both globally and locally. Using inhomogeneous diffusion and total variation regularization as examples for localized regularization schemes, we present an efficient method for locally adaptive image denoising. As expected, the smoothing parameter serves as an edge detector in this framework. Numerical examples illustrate the usefulness of our approach. We also present an application in confocal microscopy.

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Thomas Hotz, Philipp Marnitz, Rahel Stichtenoth, Laurie Davies, Zakhar Kabluchko, Axel Munk. 2010-01-29. Locally adaptive image denoising by a statistical multiresolution criterion. https://arxiv.org/abs/1001.5447

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