
Proceedings Paper
Linear methods for input scenes restoration from signals of optical-digital pattern recognition correlatorFormat | Member Price | Non-Member Price |
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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
Published in SPIE Proceedings Vol. 7340:
Optical Pattern Recognition XX
David P. Casasent; Tien-Hsin Chao, Editor(s)
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)
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)
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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