Pregled bibliografske jedinice broj: 748642
Fast and Reliable Noise Estimation for Hyperspectral Subspace Identification
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)
CROSBI ID: 748642 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
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
Projekti:
037-1193086-2771 - Numeričke metode u geofizičkim modelima (Singer, Saša, MZOS ) ( CroRIS)
Ustanove:
Prirodoslovno-matematički fakultet, Matematički odjel, Zagreb
Profili:
Vedran Novaković
(autor)
Citiraj ovu publikaciju:
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