Robust Multiple Reblurred-Based CT Image Enhancement

Ruihua Liu *

School of Mathematics and Statistics, Chongqing University of Technology, Chongqing, 400054, China.

Yijie Chen

Radiation Department, Zhengzhou First People's Hospital, Henan, 450000, China.

Jian wei

School of Mathematics and Statistics, Southwest University, Chongqing, 400715, China.

*Author to whom correspondence should be addressed.


Abstract

In this paper, we present a new algorithm for solving the blind deconvolution problem. In our method, we reblur a given degraded CT image with R different, but known PSFs, and get R different degraded CT images. Then we blindly deblur using the R new degraded CT images. Also, we introduce Bilateral Total Variation regularization term. In computer simulations in Matlab, it is the most advantages of our proposed algorithm that it performs more effectively than M. Jiang’s ENR method.

Keywords: Image enhancement, blind deconvolution, degraded image, reblurring


How to Cite

Liu, Ruihua, Yijie Chen, and Jian wei. 2014. “Robust Multiple Reblurred-Based CT Image Enhancement”. Journal of Advances in Mathematics and Computer Science 5 (3):302-9. https://doi.org/10.9734/BJMCS/2015/13749.

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