http://www.cnr.it/ontology/cnr/individuo/prodotto/ID80663

Assessment of quality parameters for a new generation hyperspectral imager (Contributo in atti di convegno)

Type

Contributo in atti di convegno (Classe)
Prodotto della ricerca (Classe)

Label

Assessment of quality parameters for a new generation hyperspectral imager (Contributo in atti di convegno) (literal)

Anno

2007-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

10.1117/12.739486 (literal)

Alternative label

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, D. Guzzi, P. Marcoionni, I. Pippi, M. Selva (2007)
Assessment of quality parameters for a new generation hyperspectral imager
in SPIE Europe International Symposium on Remote Sensing 2007, Firenze, Italia, 17-21 Settembre 2007
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, D. Guzzi, P. Marcoionni, I. Pippi, M. Selva (literal)

Pagina inizio

67480Q-1 (literal)

Pagina fine

67480Q-12 (literal)

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Volume pubblicato nell'Ottobre 2007. (literal)

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http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=824100 (literal)

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Proceedings of SPIE Remote Sensing Europe 2007, Image and Signal Processing for Remote Sensing XIII (literal)

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6748 (literal)

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6748 (literal)

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Atti pubblicati in: SPIE Vol. 6748, Image and Signal Processing for Remote Sensing XIII, L. Bruzzone (Ed.), n. 67480Q, Oct. 2007. (literal)

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12 (literal)

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Lavoro che propone una stima dei parametri di rumore e di informazione, aatraverso metodi avanzati che utilizzano concetti base della teoria dell'informazione, di immagini acquisite da un sensore di nuova generazione (Hyper-SIMGA). (literal)

Note

ISI Web of Science (WOS) (literal)
Scopu (literal)

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IFAC-CNR (literal)

Titolo

Assessment of quality parameters for a new generation hyperspectral imager (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

978-0-8194-6906-9 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume

L. Bruzzone (literal)

Abstract

This work focuses on an assessment of quality parameters characterizing a hyperspectral image collected by a newgeneration high-resolution sensor named Hyper-SIMGA, which is a spectrometer operating in the push-broom configuration. By resorting to Shannon's information theory, the concept of quality is related to the information conveyed to a user by the hyperspectral data, which can be objectively defined from both the signal-to-noise ratio (SNR) and the mutual information between the unknown noise-free digitized signal and the corresponding noise-affected observed digital samples. The estimation of the mutual information has been exploited by resorting to a lossless data compression of the dataset. In fact, the bit-rate achieved by the reversible compression process is a suitable approximation of the decorrelated data entropy, which takes into account both the contribution of the \"observation\" noise, i.e. information regarded as statistical uncertainty, whose relevance is null to a user, and the intrinsic information of hypothetically noise-free samples. Noise estimation can be obtained once a suitable parametric model of the noise, assumed to be possibly non-Gaussian, has been preliminarily determined. Noise amplitude has been assessed by means of two independent estimators relying on two automatic procedures based on a scatterplot method and a bit-plane algorithm. Noise autocorrelation has been taken into account on the three allowed directions of the available datavolume. Results are reported and discussed employing a hyperspectral image (768 spectral bands) recorded by the new Hyper-SIMGA imaging spectrometer. (literal)

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