About: Anisotropic osmosis filtering for shadow removal in images

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Anisotropic osmosis filtering for shadow removal in images
Creator	Weickert, Joachim Calatroni, Luca Caliari, Marco Parisotto, Simone Schönlieb, Carola-Bibiane
source	ArXiv
abstract	We present an anisotropic extension of the isotropic osmosis model that has been introduced by Weickert et al.~(Weickert, 2013) for visual computing applications, and we adapt it specifically to shadow removal applications. We show that in the integrable setting, linear anisotropic osmosis minimises an energy that involves a suitable quadratic form which models local directional structures. In our shadow removal applications we estimate the local structure via a modified tensor voting approach (Moreno, 2012) and use this information within an anisotropic diffusion inpainting that resembles edge-enhancing anisotropic diffusion inpainting (Weickert, 2006, Gali/'c, 2008). Our numerical scheme combines the nonnegativity preserving stencil of Fehrenbach and Mirebeau (Fehrenbach, 2014) with an exact time stepping based on highly accurate polynomial approximations of the matrix exponential. The resulting anisotropic model is tested on several synthetic and natural images corrupted by constant shadows. We show that it outperforms isotropic osmosis, since it does not suffer from blurring artefacts at the shadow boundaries.
has issue date	2018-09-17(xsd:dateTime)
bibo:doi	10.1088/1361-6420/ab08d2
has license	arxiv
sha1sum (hex)	9113e69103bd93275f8803a8ea41375c713aa9a3
schema:url	https://doi.org/10.1088/1361-6420/ab08d2
resource representing a document's title	Anisotropic osmosis filtering for shadow removal in images
resource representing a document's body	covid:9113e69103bd93275f8803a8ea41375c713aa9a3#body_text
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