Fast classified pansharpening with spectral and spatial distortion optimization (Contributo in atti di convegno)

Type
Label
  • Fast classified pansharpening with spectral and spatial distortion optimization (Contributo in atti di convegno) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/IGARSS.2012.6351614 (literal)
Alternative label
  • Luciano Alparone, Bruno Aiazzi, Stefano Baronti, Andrea Garzelli (2012)
    Fast classified pansharpening with spectral and spatial distortion optimization
    in IEEE IGARSS 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium, Monaco di Baviera, Germania, 22-27 Luglio 2012
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Luciano Alparone, Bruno Aiazzi, Stefano Baronti, Andrea Garzelli (literal)
Pagina inizio
  • 154 (literal)
Pagina fine
  • 157 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6351614&contentType=Conference+Publications&refinements%3D4294595554%2C4282331638%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6350328%29 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of IEEE IGARSS 2012: Remote Sensing for a Dynamic Earth (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 4 (literal)
Note
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Dept. Electron. & Telecomm, University of Florence, 50139 Florence, Italy IFAC-CNR, Research Area of Florence, 50019, Florence, Italy Dept. Information Engineering, University of Siena, 53100 Siena, Italy IFAC-CNR, Research Area of Florence, 50019, Florence, Italy (literal)
Titolo
  • Fast classified pansharpening with spectral and spatial distortion optimization (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-4673-1158-8 (literal)
Abstract
  • This paper presents a fast method suitable for pansharpening of MS imagery. Key points of the novel method, which falls in the category of component substitution (CS) methods, are optimization of the intensity component, achieved through multivariate regression of Pan to MS, and adjustment of the modulus of the spatial detail vector to be injected, based on a minimization of spatial distortion. Spatial distortion is measured at full scale according to the QNR protocol on land cover classes defined by NDVI thresholding. Experiments carried out on IKONOS data demonstrate that results are competitive with those of the most advanced methods, with a computational complexity comparable with that of Brovey transform fusion, which is the baseline version of the proposed method. (literal)
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