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Proceedings Paper

Image estimation based on depth-variant imaging model in three-dimensional microscopy
Author(s): Qingchuan Tao D.V.M.; Xiaohai He; Jia Zhao; Qizhi Teng; Jianguo Chen
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Paper Abstract

An algorithm for maximum-likelihood image restoration based on the expectation maximization (EM) algorithm is proposed in this paper. This estimation is based on a depth-variant imaging model in three-dimensional optical sectioning microscopy. As a result of the refractive index mismatch between the immersion medium and the mounting medium of the specimen, the imaging model in three-dimensional optical-sectioning microscopy incorporates spherical aberration that worsens with increasing depth under the coverslip and changes in the point spread function (PSF). Two-dimension images restoration and three-dimension serial images restoration are to be used to analyze the capability of the EM-ML algorithm, and the performance shows that the EM-ML algorithm can restore the blurred of image by the depth variant image model.

Paper Details

Date Published: 8 February 2005
PDF: 9 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.577515
Show Author Affiliations
Qingchuan Tao D.V.M., Sichuan Univ. (China)
Xiaohai He, Sichuan Univ. (China)
Jia Zhao, Sichuan Univ. (China)
Qizhi Teng, Sichuan Univ. (China)
Jianguo Chen, Sichuan Univ. (China)


Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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