期刊
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION
卷 21, 期 9, 页码 1593-1601出版社
OPTICAL SOC AMER
DOI: 10.1364/JOSAA.21.001593
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- NIGMS NIH HHS [R01 GM55708, 5R01 GM4979808] Funding Source: Medline
We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maximization (EM) formalism by using a new approximate model for depth-varying image formation for optical sectioning microscopy. This new strata-based model incorporates spherical aberration that worsens as the microscope is focused deeper under the cover slip and is the result of the refractive-index mismatch between the immersion medium and the mounting medium of the specimen. Images of a specimen with known geometry and refractive index show that the model captures the main features of the image. We analyze the performance of the depth-variant EM algorithm with simulations, which show that the algorithm can compensate for image degradation changing with depth. (C) 2004 Optical Society of America.
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