Naslov
Deterministic Blind Source Separation for Space Variant Imaging

Autori
Szu, Harold ; Kopriva, Ivica

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proc. of the Fourth International Symposium on Independent Component Analysis and Blind Signal Separation / S.I. Amari, A.Cichocki, S. Makino, N. Murata - Nara, 2003, 669-674

Skup
Fourth International Symposium on Independent Component Analysis and Blind Signal Separation

Mjesto i datum
Nara-shi, Japan, 01.04.2003. - 04.04.2003

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Independent component analysis; Space variant imaging; Helmholtz free energy;

Sažetak
We consider a deterministic approach to the noise free blind image separation and deconvolution problem with positivity constraints. This is necessary because in some real world applications (telescope images in astronomy, remotely sensed images, etc.) the pixel values correspond to intensities and must be positive. Also mixing matrix itself must be positive if it for example represents point spread function of an imaging system in astronomy or spectral reflectance matrix in remote sensing. In related papers the blind source separation (BSS) problem with positivity constraints is being solved by using probabilistic approach assuming independence between the sources that requires use of all the pixel data. Implicit assumption of this approach is that unknown mixing matrix is space invariant. Here we propose solution that is determinis tic and solves the problem on the pixel by pixel basis. Consequently, algorithm is capable to solve the space variant problems. This is accomplished by minimizing the 2nd law of thermodynamics based contrast function called Helmholtz free energy. Formulation of our algorithm is equivalent to the MaxEnt formulation of the supervised separation problem with essential difference that the mixing matrix is unknown in our case. We demonstrate the algorithm capability to perfectly recover images from the synthetic noise free linear mixture of two images.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

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