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Proceedings Paper

Linear methods for input scenes restoration from signals of optical-digital pattern recognition correlator
Author(s): Sergey N. Starikov; Mikhail V. Konnik; Edward A. Manykin; Vladislav G. Rodin
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Paper Abstract

Linear methods of restoration of input scene's images in optical-digital correlators are described. Relatively low signal to noise ratio of a camera's photo sensor and extensional PSF's size are special features of considered optical-digital correlator. RAW-files of real correlation signals obtained by digital photo sensor were used for input scene's images restoration. It is shown that modified evolution method, which employs regularization by Tikhonov, is better among linear deconvolution methods. As a regularization term, an inverse signal to noise ratio as a function of spatial frequencies was used. For additional improvement of restoration's quality, noise analysis of boundary areas of the image to be reconstructed was performed. Experimental results on digital restoration of input scene's images are presented.

Paper Details

Date Published: 13 April 2009
PDF: 9 pages
Proc. SPIE 7340, Optical Pattern Recognition XX, 73400B (13 April 2009); doi: 10.1117/12.818458
Show Author Affiliations
Sergey N. Starikov, Moscow Engineering Physics Institute (Russian Federation)
Mikhail V. Konnik, Moscow Engineering Physics Institute (Russian Federation)
Edward A. Manykin, Moscow Engineering Physics Institute (Russian Federation)
Vladislav G. Rodin, Moscow Engineering Physics Institute (Russian Federation)


Published in SPIE Proceedings Vol. 7340:
Optical Pattern Recognition XX
David P. Casasent; Tien-Hsin Chao, Editor(s)

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