Stochastic Resonance Based Visual Perception Using Spiking Neural Networks.

Abstract:

:Our aim is to propose an efficient algorithm for enhancing the contrast of dark images based on the principle of stochastic resonance in a global feedback spiking network of integrate-and-fire neurons. By linear approximation and direct simulation, we disclose the dependence of the peak signal-to-noise ratio on the spiking threshold and the feedback coupling strength. Based on this theoretical analysis, we then develop a dynamical system algorithm for enhancing dark images. In the new algorithm, an explicit formula is given on how to choose a suitable spiking threshold for the images to be enhanced, and a more effective quantifying index, the variance of image, is used to replace the commonly used measure. Numerical tests verify the efficiency of the new algorithm. The investigation provides a good example for the application of stochastic resonance, and it might be useful for explaining the biophysical mechanism behind visual perception.

journal_name

Front Comput Neurosci

authors

Fu Y,Kang Y,Chen G

doi

10.3389/fncom.2020.00024

subject

Has Abstract

pub_date

2020-05-15 00:00:00

pages

24

issn

1662-5188

journal_volume

14

pub_type

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