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Journal of Biomedical Optics

New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model
Author(s): Zhaoxue Chen; Hao Chen
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Paper Abstract

A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy–Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.

Paper Details

Date Published: 11 July 2014
PDF: 9 pages
J. Biomed. Opt. 19(7) 076009 doi: 10.1117/1.JBO.19.7.076009
Published in: Journal of Biomedical Optics Volume 19, Issue 7
Show Author Affiliations
Zhaoxue Chen, Univ. of Shanghai for Science and Technology (China)
Hao Chen, Univ. of Shanghai for Science and Technology (China)

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