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Pregled bibliografske jedinice broj: 748642

Fast and Reliable Noise Estimation for Hyperspectral Subspace Identification


Benner, Peter; Novaković, Vedran; Plaza, Antonio; Quintana- Ortí, Enrique S.; Remón, Alfredo
Fast and Reliable Noise Estimation for Hyperspectral Subspace Identification // IEEE geoscience and remote sensing letters, 12 (2015), 6; 1199-1203 doi:10.1109/LGRS.2014.2388133 (međunarodna recenzija, članak, znanstveni)


Naslov
Fast and Reliable Noise Estimation for Hyperspectral Subspace Identification

Autori
Benner, Peter ; Novaković, Vedran ; Plaza, Antonio ; Quintana- Ortí, Enrique S. ; Remón, Alfredo

Izvornik
IEEE geoscience and remote sensing letters (1545-598X) 12 (2015), 6; 1199-1203

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Hyperspectral imaging; subspace identification; noise estimation; least square problems; multicore processors

Sažetak
In this letter, we introduce an efficient algorithm to estimate the noise correlation matrix in the initial stage of the hyperspectral signal identification by minimum error (HySime) method, commonly used for signal subspace identification in remotely sensed hyperspectral images. Compared with the current implementations of this stage, the new algorithm for noise estimation relies on the reliable QR factorization, producing correct results even when operating with single- precision arithmetic. Additionally, our algorithm exhibits a lower computational cost, and it is highly parallel. The experiments on a multicore server, using two real hyperspectral scenes, expose that these theoretical advantages carry over to the practical results.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Geologija, Računarstvo



POVEZANOST RADA


Projekt / tema
037-1193086-2771 - Numeričke metode u geofizičkim modelima (Saša Singer, )

Ustanove
Prirodoslovno-matematički fakultet, Matematički odjel, Zagreb

Autor s matičnim brojem:
Vedran Novaković, (308820)

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Uključenost u ostale bibliografske baze podataka:


  • INSPEC


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