Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case

Detalhes bibliográficos
Autor(a) principal: Araújo, Adérito
Data de Publicação: 2017
Outros Autores: Barbeiro, Sílvia, Cuesta, Eduardo, Durán, Angel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/44984
https://doi.org/10.1007/s10851-017-0721-9
Resumo: In this paper we study the application of 2×2 nonlinear cross-diffusion systems as mathematical models of image filtering. These are systems of two nonlinear, coupled partial differential equations of parabolic type. The nonlinearity and cross-diffusion character are provided by a nondiagonal matrix of diffusion coefficients that depends on the variables of the system. We prove the well-posedness of an initial-boundary-value problem with Neumann boundary conditions and uniformly positive definite cross-diffusion matrix. Under additional hypotheses on the coefficients, the models are shown to satisfy the scale-space properties of shift, contrast, average grey and translational invariances. The existence of Lyapunov functions and the asymptotic behaviour of the solutions are also studied. According to the choice of the cross-diffusion matrix (on the basis of the results on filtering with linear cross-diffusion, discussed by the authors in a companion paper and the use of edge stopping functions ) the performance of the models is compared by computational means in a filtering problem. The numerical results reveal differences in the evolution of the filtering as well as in the quality of edge detection given by one of the components of the system, in terms of the cross-diffusion matrix.
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spelling Cross-Diffusion Systems for Image Processing: II. The Nonlinear CaseIn this paper we study the application of 2×2 nonlinear cross-diffusion systems as mathematical models of image filtering. These are systems of two nonlinear, coupled partial differential equations of parabolic type. The nonlinearity and cross-diffusion character are provided by a nondiagonal matrix of diffusion coefficients that depends on the variables of the system. We prove the well-posedness of an initial-boundary-value problem with Neumann boundary conditions and uniformly positive definite cross-diffusion matrix. Under additional hypotheses on the coefficients, the models are shown to satisfy the scale-space properties of shift, contrast, average grey and translational invariances. The existence of Lyapunov functions and the asymptotic behaviour of the solutions are also studied. According to the choice of the cross-diffusion matrix (on the basis of the results on filtering with linear cross-diffusion, discussed by the authors in a companion paper and the use of edge stopping functions ) the performance of the models is compared by computational means in a filtering problem. The numerical results reveal differences in the evolution of the filtering as well as in the quality of edge detection given by one of the components of the system, in terms of the cross-diffusion matrix.Springer2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/44984http://hdl.handle.net/10316/44984https://doi.org/10.1007/s10851-017-0721-9https://doi.org/10.1007/s10851-017-0721-9enghttps://doi.org/10.1007/s10851-017-0721-9Araújo, AdéritoBarbeiro, SílviaCuesta, EduardoDurán, Angelinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2021-06-29T10:02:54Zoai:estudogeral.uc.pt:10316/44984Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:53:27.094238Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
title Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
spellingShingle Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
Araújo, Adérito
title_short Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
title_full Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
title_fullStr Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
title_full_unstemmed Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
title_sort Cross-Diffusion Systems for Image Processing: II. The Nonlinear Case
author Araújo, Adérito
author_facet Araújo, Adérito
Barbeiro, Sílvia
Cuesta, Eduardo
Durán, Angel
author_role author
author2 Barbeiro, Sílvia
Cuesta, Eduardo
Durán, Angel
author2_role author
author
author
dc.contributor.author.fl_str_mv Araújo, Adérito
Barbeiro, Sílvia
Cuesta, Eduardo
Durán, Angel
description In this paper we study the application of 2×2 nonlinear cross-diffusion systems as mathematical models of image filtering. These are systems of two nonlinear, coupled partial differential equations of parabolic type. The nonlinearity and cross-diffusion character are provided by a nondiagonal matrix of diffusion coefficients that depends on the variables of the system. We prove the well-posedness of an initial-boundary-value problem with Neumann boundary conditions and uniformly positive definite cross-diffusion matrix. Under additional hypotheses on the coefficients, the models are shown to satisfy the scale-space properties of shift, contrast, average grey and translational invariances. The existence of Lyapunov functions and the asymptotic behaviour of the solutions are also studied. According to the choice of the cross-diffusion matrix (on the basis of the results on filtering with linear cross-diffusion, discussed by the authors in a companion paper and the use of edge stopping functions ) the performance of the models is compared by computational means in a filtering problem. The numerical results reveal differences in the evolution of the filtering as well as in the quality of edge detection given by one of the components of the system, in terms of the cross-diffusion matrix.
publishDate 2017
dc.date.none.fl_str_mv 2017
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dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/44984
http://hdl.handle.net/10316/44984
https://doi.org/10.1007/s10851-017-0721-9
https://doi.org/10.1007/s10851-017-0721-9
url http://hdl.handle.net/10316/44984
https://doi.org/10.1007/s10851-017-0721-9
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