Spectral Distortion Evaluation in Lossy Compression of Hyperspectral Imagery (Contributo in atti di convegno)

Type
Label
  • Spectral Distortion Evaluation in Lossy Compression of Hyperspectral Imagery (Contributo in atti di convegno) (literal)
Anno
  • 2003-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/IGARSS.2003.1294260 (literal)
Alternative label
  • Aiazzi B., Alparone L., Baronti S., Lastri C., Santurri L., Selva M. (2003)
    Spectral Distortion Evaluation in Lossy Compression of Hyperspectral Imagery
    in IGARSS 2003 - IEEE International Geoscience and Remote Sensing Symposium, Tolosa, Francia, 21-25 Luglio 2003
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Aiazzi B., Alparone L., Baronti S., Lastri C., Santurri L., Selva M. (literal)
Pagina inizio
  • 1817 (literal)
Pagina fine
  • 1819 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1294260 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of IEEE IGARSS 2003: Learning from Earth's shapes and colors (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 3 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • Proceedings of IGARSS 2003, the IEEE Inc., Piscataway, NJ, USA, 2003, versione CD-ROM, vol. 3, pp. 1817-1819 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 3 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IFAC-CNR (literal)
Titolo
  • Spectral Distortion Evaluation in Lossy Compression of Hyperspectral Imagery (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 0-7803-7929-2 (literal)
Abstract
  • Goal of this work is to investigate lossy compression methodologies from the viewpoint of spectral distortion introduced in hyperspectral pixel vectors, besides that of radiometric distortion. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is perhaps the main source of spectral information. Therefore, whenever a lossless compression is not practicable, near-lossless compression is recommended in such applications where spectral quality is crucial. (literal)
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