Naslov
Non-Negative Matrix Factorization Approach to Blind Image Deconvolution

Autori
Kopriva, Ivica ; Nuzillard, Danielle

Izvornik
Lecture notes in computer science (0302-9743) 3889 (2006); 966-973

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

Ključne riječi
Blind deconvolution ; Nonegative matrix factorization ; Independent component analysis
(Non-Negative Matrix Factorization Approach to Blind Image Deconvolution)

Sažetak
Novel approach to single frame multichannel blind image deconvolution is formulated recently as non-negative matrix factorization (NMF) problem with sparseness constraints imposed on the unknown mixing vector. Unlike most of the blind image deconvolution algorithms, the NMF approach requires no a priori knowledge about the blurring kernel and original image. Experimental performance evaluation of the NMF algorithm is presented with the image degraded by the out-of-focus blur. NMF algorithm is compared with the state-of-the-art single frame blind image deconvolution algorithm: blind Richardson-Lucy algorithm and single frame multichannel independent component analysis based algorithm. It has been demonstrated that NMF approach outperforms mentioned blind image deconvolution methods.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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