Locally adaptive image denoising by a statistical multiresolution criterion

Thomas Hotz, Philipp Marnitz, Rahel Stichtenoth, Laurie Davies, Zakhar Kabluchko and Axel Munk

Computational Statistics & Data Analysis, 2012, vol. 56, issue 3, 543-558

Abstract: It is shown how to 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, an efficient method for locally adaptive image denoising is presented. As expected, the smoothing parameter serves as an edge detector in this framework. Numerical examples together with applications in confocal microscopy illustrate the usefulness of the approach.

Keywords: Image reconstruction; Statistical multiresolution criterion; Bandwidth selection (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:3:p:543-558

DOI: 10.1016/j.csda.2011.08.018

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