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Автор Rafael Navarro
Автор Oscar Nestares
Автор Jose J Valles
Дата выпуска 2004-01-01
dc.description We present a novel Bayesian method for pattern recognition in images affected by unknown optical degradations and additive noise. The method is based on a multiscale/multiorientation subband decomposition of both the matched filter (original object) and the degraded images. Using this image representation within the Bayesian framework, it is possible to make a coarse estimation of the unknown optical transfer function, which strongly simplifies the Bayesian estimation of the original pattern that most probably generated the observed image. The method has been implemented and compared to other previous methods through a realistic simulation. The images are degraded by different levels of both random (atmospheric turbulence) and deterministic (defocus) optical aberrations, as well as additive white Gaussian noise. The Bayesian method proved to be highly robust to both optical blur and noise, providing rates of correct responses significantly better than previous methods.
Формат application.pdf
Издатель Institute of Physics Publishing
Копирайт IOP Publishing Ltd
Название Bayesian pattern recognition in optically degraded noisy images
Тип paper
DOI 10.1088/1464-4258/6/1/008
Electronic ISSN 1741-3567
Print ISSN 1464-4258
Журнал Journal of Optics A: Pure and Applied Optics
Том 6
Первая страница 36
Последняя страница 42
Аффилиация Rafael Navarro; Instituto de Óptica ‘Daza de Valdés’, Consejo Superior de Investigaciones Científicas, Serrano 121, 28006 Madrid, Spain
Аффилиация Oscar Nestares; Instituto de Óptica ‘Daza de Valdés’, Consejo Superior de Investigaciones Científicas, Serrano 121, 28006 Madrid, Spain
Аффилиация Jose J Valles; Instituto de Óptica ‘Daza de Valdés’, Consejo Superior de Investigaciones Científicas, Serrano 121, 28006 Madrid, Spain
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