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Noisy Image Super-resolution by Artificial Neural Networks (CROSBI ID 488770)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Szu, Harold ; Kopriva, Ivica ; Noisy Image Super-resolution by Artificial Neural Networks // Proceedings of the SPIE 4391 / Szu, Harold ; Buss, James ; (ur.). Bellingham (WA): SPIE, 2001. str. 16-20-x

Podaci o odgovornosti

Szu, Harold ; Kopriva, Ivica ;

engleski

Noisy Image Super-resolution by Artificial Neural Networks

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. Our success is perhaps due to the Blind Source Separation (BSS) Smart-Pixel Detectors (SPD) behind the imaging lens (inverse adaptation), while the Rayleigh diffraction limit remains valid for a single instance of the deterministic imaging systems&#8217 ; realization.

Independent Component Analysis; Superresolution; Blind Source Demixing; Focal Plane Arrays.

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Podaci o prilogu

16-20-x.

2001.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the SPIE 4391

Szu, Harold ; Buss, James ;

Bellingham (WA): SPIE

Podaci o skupu

SPIE AeroSense Symposium - Wavelet Applicatios VIII

predavanje

16.04.2001-20.04.2001

Orlando (FL), Sjedinjene Američke Države

Povezanost rada

Elektrotehnika