title: Quantum-implementable selective reconstruction of high-resolution images.
abstract: This paper, written for interdisciplinary audience, presents computational image reconstruction implementable by quantum optics. The input-triggered selection of a high-resolution image among many stored ones, and its reconstruction if the input is occluded or noisy, has been successfully simulated. The original algorithm, based on the Hopfield associative neural net, was transformed in order to enable its quantum-wave implementation based on holography. The main limitations of the classical Hopfield net are much reduced with the simulated new quantum-optical implementation.
authors.affiliation: Institute for Computer Vision and Graphics, Graz University of Technology, A-8010 Graz, Austria. perus@icg.tu-graz.ac.at
authors.forename: Mitja
authors.initials: M
authors.lastname: Perus
authors.forename: Horst
authors.initials: H
authors.lastname: Bischof
authors.forename: H John
authors.initials: HJ
authors.lastname: Caulfield
authors.forename: Chu Kiong
authors.initials: CK
authors.lastname: Loo