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23 September 2019 Dynamic linear threshold attenuation linking synaptic computing network for image enhancement
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Abstract

Dynamic linear threshold attenuation linking synaptic computing network (DLSCN) is proposed. The attenuation rate of neural threshold determines the propagation rate of the gamma band. DLSCN employs clustering to segment the external input stimuli of neurons in intensity. Different attenuation rates are set in different intensity stimulus regions to control the propagation rate of the gamma band. Therefore, the ignition timing of neurons can be delayed or advanced so as to obtain the expected distribution of linking synaptic. The intensity distribution of the output image of the network is more consistent with the characteristics of the human visual system. Experiments on four public datasets show that DLSCN achieves good results in enhancing image contrast and boosting image details.

© 2019 SPIE and IS&T 1017-9909/2019/$28.00 © 2019 SPIE and IS&T
Ping Gao, Longjie Li, and Xiaoyun Chen "Dynamic linear threshold attenuation linking synaptic computing network for image enhancement," Journal of Electronic Imaging 28(5), 053010 (23 September 2019). https://doi.org/10.1117/1.JEI.28.5.053010
Received: 29 May 2019; Accepted: 6 September 2019; Published: 23 September 2019
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