Divide-and-conquer strategies for hyperspectral image processing : a review of their benefits and advantages
Blanes Garcia, Ian (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)
Marcellin, Michael W. (University of Arizona)
Bartrina Rapesta, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)

Data:	2012
Resum:	In the field of geophysics, huge volumes of information often need to be processed with complex and time-consuming algorithms to better understand the nature of the data at hand. A particularly useful instrument within a geophysicists toolbox is a set of decorrelating transforms. Such transforms play a key role in the acquisition and processing of satellite-gathered information, and notably in the processing of hyperspectral images. Satellite images have a substantial amount of redundancy that not only renders the true nature of certain events less perceivable to geophysicists but also poses an issue to satellite makers, who have to exploit this data redundancy in the design of compression algorithms due to the constraints of down-link channels. This issue is magnified for hyperspectral imaging sensors, which capture hundreds of visual representations of a given targeteach representation (called a component or a band) for a small range of the light spectrum. Although seldom alone, decorrelation transforms are often used to alleviate this situation by changing the original data space into a representation where redundancy is decreased and valuable information is more apparent.
Ajuts:	European Commission 242390 European Commission 250420 Ministerio de Ciencia e Innovación TIN2009-14426-C02-01 Ministerio de Educación, Cultura y Deporte FPU-AP2007-015553 Agència de Gestió d'Ajuts Universitaris i de Recerca 2009/SGR-1224
Drets:	Tots els drets reservats.
Llengua:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Matèria:	Geophysical image processing ; Remote sensing
Publicat a:	IEEE signal processing magazine, Vol. 29, Issue 3, (May 2012) , p. 71-81

DOI: 10.1109/MSP.2011.2179416

Post-print 22 p, 2.3 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Enginyeries > Group on Interactive Coding of Images (GICI)
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