Pregled bibliografske jedinice broj: 108642
Artificial neural networks for noisy image super-resolution
Artificial neural networks for noisy image super-resolution // Optics Communications, 198 (2001), 1-3; 71-81 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 108642 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Artificial neural networks for noisy image super-resolution
Autori
Szu, Harold ; Kopriva, Ivica
Izvornik
Optics Communications (0030-4018) 198
(2001), 1-3;
71-81
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
independent component analysis; optical diffraction; Fourier optics; unsupervised neural networks; image processing
Sažetak
Noisy incoherent objects, which are too close to be remotely separated by optically imaging beyond the Rayleigh diffraction limit, might be resolved by employing the Artificial Neural Network (ANN) smart pixel post processing and its mathematical framework, Independent Component Analysis (ICA). It is shown that ICA ANN approach to superresolution based on information maximization principle could be seen as a part of the general approach called space-bandwidth (SW) product adaptation method.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
036024
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Ivica Kopriva
(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::
- Chemical Abstracts
- EI Compendex Plus
- Engineering Indeks
- INSPEC
- Scopus
