AUTHOR=Fu Yuxuan , Kang Yanmei , Chen Guanrong TITLE=Stochastic Resonance Based Visual Perception Using Spiking Neural Networks JOURNAL=Frontiers in Computational Neuroscience VOLUME=14 YEAR=2020 URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2020.00024 DOI=10.3389/fncom.2020.00024 ISSN=1662-5188 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.