• español
  • English
  • français
  • Deutsch
  • português (Brasil)
  • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Parcourir

    Tout UVaDOCCommunautésPar date de publicationAuteursSujetsTitres

    Mon compte

    Ouvrir une session

    Statistiques

    Statistiques d'usage de visualisation

    Compartir

    Voir le document 
    •   Accueil de UVaDOC
    • PUBLICATIONS SCIENTIFIQUES
    • Departamentos
    • Dpto. Matemática Aplicada
    • DEP51 - Artículos de revista
    • Voir le document
    •   Accueil de UVaDOC
    • PUBLICATIONS SCIENTIFIQUES
    • Departamentos
    • Dpto. Matemática Aplicada
    • DEP51 - Artículos de revista
    • Voir le document
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano

    Exportar

    RISMendeleyRefworksZotero
    • edm
    • marc
    • xoai
    • qdc
    • ore
    • ese
    • dim
    • uketd_dc
    • oai_dc
    • etdms
    • rdf
    • mods
    • mets
    • didl
    • premis

    Citas

    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/64441

    Título
    Cross-diffusion based filtering as pre-processing step for remote sensing procedures
    Autor
    Cuesta Montero, EduardoAutoridad UVA Orcid
    Quintano Pastor, María del CarmenAutoridad UVA Orcid
    Fernández Manso, Alfonso
    Año del Documento
    2020-02-01
    Editorial
    ELSEVIER
    Documento Fuente
    Advances in Engineering Software, February 2020, vol. 140, 102751
    Résumé
    A new methodology combining 2 × 2 cross-diffusion systems of nonlinear partial differential equations (CDS) with classical image classification procedures is proposed in the present paper. Such a kind of mathematical models (CDS) have been theoretically studied in previous works in the context of image processing, however here they are tested and stressed in very practical instances. In particular, the main contribution of this paper is the improvement of the classification of satellite images when they are previously filtered by means of a CDS model. This conclusion is based on a wide and costly experimentation with satellite images of areas damaged by forest fires and surface coal mining, all of them located in Mediterranean areas. The efficiency of our metho- dology is not only in terms of the classification improvement but also in terms of the runtime saving since CDS based filtering is much less costly than other classical partial differential equations based filtering mathematical models as for example anisotropic models or higher order ones, always within the framework of nonlinear partial differential equations.
    Palabras Clave
    Cross-diffusion systems; Image filtering; Remote sensing
    Revisión por pares
    SI
    DOI
    10.1016/j.advengsoft.2019.102751
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/64441
    Tipo de versión
    info:eu-repo/semantics/submittedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP51 - Artículos de revista [145]
    Afficher la notice complète
    Fichier(s) constituant ce document
    Nombre:
    2020-ECuesta.pdf
    Tamaño:
    882.6Ko
    Formato:
    Adobe PDF
    Thumbnail
    Voir/Ouvrir
    Attribution-NonCommercial-NoDerivatives 4.0 InternacionalExcepté là où spécifié autrement, la license de ce document est décrite en tant que Attribution-NonCommercial-NoDerivatives 4.0 Internacional

    Universidad de Valladolid

    Powered by MIT's. DSpace software, Version 5.10