Web of Science: 14 citas, Scopus: 17 citas, Google Scholar: citas
Diffusion-based inpainting for coding remote-sensing data
Amrani, Naoufal (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Peter, Pascal (Saarland University (Alemanya). Mathematical Image Analysis Group)
Weickert, Joachim (Saarland University (Alemanya). Mathematical Image Analysis Group)

Fecha: 2017
Resumen: Inpainting techniques based on partial differential equations (PDEs) such as diffusion processes are gaining growing importance as a novel family of image compression methods. Nevertheless, the application of inpainting in the field of hyperspectral imagery has been mainly focused on filling in missing information or dead pixels due to sensor failures. In this paper we propose a novel PDE-based inpainting algorithm to compress hyperspectral images. The method inpaints separately the known data in the spatial and in the spectral dimensions. Then it applies a prediction model to the final inpainting solution to obtain a representation much closer to the original image. Experimental results over a set of hyperspectral images indicate that the proposed algorithm can perform better than a recent proposed extension to prediction-based standard CCSDS-123. 0 at low bitrate, better than JPEG 2000 Part 2 with the DWT 9/7 as a spectral transform at all bit-rates, and competitive to JPEG 2000 with principal component analysis (PCA), the optimal spectral decorrelation transform for Gaussian sources.
Ayudas: Ministerio de Economía y Competitividad TIN2015-71126-R
Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-691
Derechos: Tots els drets reservats.
Lengua: Anglès
Documento: Article ; recerca ; Versió acceptada per publicar
Publicado en: IEEE geoscience and remote sensing letters, Vol. PP, issue 99 (June 2017) , ISSN 1545-598X

DOI: 10.1109/LGRS.2017.2702106


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El registro aparece en las colecciones:
Documentos de investigación > Documentos de los grupos de investigación de la UAB > Centros y grupos de investigación (producción científica) > Ingeniería > Group on Interactive Coding of Images (GICI)
Artículos > Artículos de investigación
Artículos > Artículos publicados

 Registro creado el 2017-04-30, última modificación el 2023-07-14



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