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Spiking cortical model-based noise detector for switching-based filters

[+] Author Affiliations
Xuming Zhang

Huazhong University of Science and Technology, School of Life Science and Technology, No. 1037, Luoyu Road, Wuhan, China

Yu Xiao

Central China Normal University, School of Life Science, No. 152, Luoyu Road, Wuhan, China

Wenguang Hou

Huazhong University of Science and Technology, School of Life Science and Technology, No. 1037, Luoyu Road, Wuhan, China

Yi Zhan

Huazhong University of Science and Technology, School of Life Science and Technology, No. 1037, Luoyu Road, Wuhan, China

Mingyue Ding

Huazhong University of Science and Technology, School of Life Science and Technology, No. 1037, Luoyu Road, Wuhan, China

Zhouping Yin

Huazhong University of Science and Technology, School of Mechanical Science and Engineering, No. 1037, Luoyu Road, Wuhan, China

J. Electron. Imaging. 21(1), 013020 (Apr 02, 2012). doi:10.1117/1.JEI.21.1.013020
History: Received October 5, 2011; Revised December 19, 2011; Accepted January 17, 2012
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Abstract.  A novel noise detector based on the spiking cortical model (SCM) is proposed for switching-based filters. In the proposed noise detector, the corrupted pixels are firstly identified as noise candidates based on the firing time of the SCM, and then the misclassified noise-free pixels are dismissed from noise candidates based on the absolute difference of the firing time between the considered neurons and their neighboring neurons. Extensive simulations show that although the proposed noise detector generally has lower computational efficiency than several state-of-the-art noise detectors, it outperforms all the compared noise detectors in noise detection accuracy by classifying the pixels in the corrupted images with very few or no mistakes at the various noise ratios.

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© 2012 SPIE and IS&T

Citation

Xuming Zhang ; Yu Xiao ; Wenguang Hou ; Yi Zhan ; Mingyue Ding, et al.
"Spiking cortical model-based noise detector for switching-based filters", J. Electron. Imaging. 21(1), 013020 (Apr 02, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.1.013020


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