Research Papers: Imaging

New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model

[+] Author Affiliations
Zhaoxue Chen

University of Shanghai for Science and Technology, School of Medical Instrument and Food Engineering, No. 516, Jungong Road, Yangpu District, Shanghai 200093, China

Hao Chen

University of Shanghai for Science and Technology, School of Medical Instrument and Food Engineering, No. 516, Jungong Road, Yangpu District, Shanghai 200093, China

J. Biomed. Opt. 19(7), 076009 (Jul 11, 2014). doi:10.1117/1.JBO.19.7.076009
History: Received March 12, 2014; Revised May 6, 2014; Accepted June 9, 2014
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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.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Zhaoxue Chen and Hao Chen
"New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model", J. Biomed. Opt. 19(7), 076009 (Jul 11, 2014). ; http://dx.doi.org/10.1117/1.JBO.19.7.076009


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