Quantum-implementable selective reconstruction of high-resolution images

Peruš, M. and Bischof, H. and Caulfield, H.J. and Loo, C.K. (2004) Quantum-implementable selective reconstruction of high-resolution images. Applied Optics, 43 (33). pp. 6134-6138. ISSN 1539-4522

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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.

Item Type: Article
Uncontrolled Keywords: Computer science; artificial intelligence; high resolution image; quantum aptics
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science & Information Technology > Dept of Artificial Intelligence
Depositing User: Miss Nur Jannatul Adnin Ahmad Shafawi
Date Deposited: 19 Mar 2013 01:16
Last Modified: 19 Mar 2013 01:16
URI: http://eprints.um.edu.my/id/eprint/5184

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