2 April 2012 Spiking cortical model-based noise detector for switching-based filters
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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.
© 2012 SPIE and IS&T
Xuming Zhang, Xuming Zhang, Wenguang W. Hou, Wenguang W. Hou, Yi Zhan, Yi Zhan, Mingyue Ding, Mingyue Ding, Yu Xiao, Yu Xiao, Zhouping Yin, Zhouping Yin, } "Spiking cortical model-based noise detector for switching-based filters," Journal of Electronic Imaging 21(1), 013020 (2 April 2012). https://doi.org/10.1117/1.JEI.21.1.013020 . Submission:
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