Quality evaluation of Hyper-spectral image data acquired by push-broom sensors (Articolo in rivista)

Type
Label
  • Quality evaluation of Hyper-spectral image data acquired by push-broom sensors (Articolo in rivista) (literal)
Anno
  • 2005-01-01T00:00:00+01:00 (literal)
Alternative label
  • Bruno Aiazzi; Stefano Baronti; Cinzia Lastri; Ivan Pippi; Leonardo Santurri; Massimo Selva (2005)
    Quality evaluation of Hyper-spectral image data acquired by push-broom sensors
    in Rivista italiana di telerilevamento (Testo stamp.)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Bruno Aiazzi; Stefano Baronti; Cinzia Lastri; Ivan Pippi; Leonardo Santurri; Massimo Selva (literal)
Pagina inizio
  • 171 (literal)
Pagina fine
  • 180 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 33/34 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • Special Number on the AIT Workshop on Hyperspectral Observations of Terrestrial Environments (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 10 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IFAC-CNR, Institute of Applied Physics IFAC-CNR, Institute of Applied Physics IFAC-CNR, Institute of Applied Physics IFAC-CNR, Institute of Applied Physics IFAC-CNR, Institute of Applied Physics IFAC-CNR, Institute of Applied Physics (literal)
Titolo
  • Quality evaluation of Hyper-spectral image data acquired by push-broom sensors (literal)
Abstract
  • This work focuses on evaluating quality and estimating the information of multi-dimensional signals and in particular of hyperspectral remote sensing image data. Lossless data compression is exploited to measure the information content of the data. In fact, the bit-rate achieved by the reversible compression process takes into account both the contribution of the noise, whose relevance is null to a user, and the information of hypothetically noise-free data. The parametric model of the noise has been preliminary estimated. Since we want to know what is the amount of information without the observation noise, an entropy model of the image source is defined and such a model is inverted. Results are reported and discussed on hyper-spectral data acquired by the CHRIS and VIRS imaging spectrometers. (literal)
Prodotto di
Autore CNR
Insieme di parole chiave

Incoming links:


Autore CNR di
Prodotto
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
Insieme di parole chiave di
data.CNR.it