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Overview of Nonlinear Partial Differential Equation-based Structural Inpainting Techniques

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dc.contributor.author BARBU, Tudor
dc.date.accessioned 2020-11-03T07:00:39Z
dc.date.available 2020-11-03T07:00:39Z
dc.date.issued 2018
dc.identifier.citation BARBU, Tudor. Overview of Nonlinear Partial Differential Equation-based Structural Inpainting Techniques. In: CAIM 2018: The 26th Conference on Applied and Industrial Mathematics: Book of Abstracts, Technical University of Moldova, September 20-23, 2018. Chişinău: Bons Offices, 2018, p. 8. en_US
dc.identifier.uri http://repository.utm.md/handle/5014/11013
dc.description Only Abstract en_US
dc.description.abstract Image interpolation, known also as inpainting or completion, represents the process of recovering the missing or highly deteriorated regions of the image, as plausibly as possible, by using the information achieved from the known surrounding areas. The inpainting techniques are divided into three main categories: structure-based, texture-based and combined reconstruction approaches. We consider only the structural image interpolation domain that comprises variational and partial differential equation (PDE) - based inpainting models. A comprehensive overview of the state of the art nonlinear diffusion-based inpainting techniques is provided here. Our own contributions to this image processing field are also highlighted. en_US
dc.language.iso en en_US
dc.publisher Bons Offices en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject structural inpainting en_US
dc.subject variational scheme en_US
dc.subject nonlinear diffusion en_US
dc.subject partial differential equation en_US
dc.subject inpainting models en_US
dc.subject images processing en_US
dc.subject finite difference method en_US
dc.subject numerical approximation en_US
dc.title Overview of Nonlinear Partial Differential Equation-based Structural Inpainting Techniques en_US
dc.type Article en_US


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