KEYWORDS: Signal to noise ratio, Stochastic processes, Visual process modeling, Human vision and color perception, Interference (communication), Image enhancement, Signal detection, Digital image processing, Brain, Data processing
Elucidation of information processing in our brains is progressing given the highly informationoriented world we live in. Noise is inevitably present in both man-made and natural systems. Previously, these elements were removed for signal detection and information processing. However, recent studies have reported that noise plays a major role in brain information processing. One of the salient features of the relationship between noise and the vision system is the stochastic resonance phenomenon, wherein the detection rate of a weak signal is improved by the visual addition of a blinking noise of appropriate intensity. Improved understanding of the vision system is very useful for the development of imaging technology. This strategy of improving weak signal detection can be applied to digital image processing. In this study, we propose a vision model based on the FitzHugh–Nagumo equation and confirm that the stochastic resonance in brightness perception can be described by the model.
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