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We report the possibility of using a simple neural network for effortlessrestoration of low-light images inspired by the retina model, which mimics theneurophysiological principles and dynamics of various types of optical neurons.The proposed neural network model saves the cost of computational overhead incontrast with traditional signal-processing models, and generates resultscomparable with complicated deep learning models from the subjective perceptualperspective. This work shows that to directly simulate the functionalities ofretinal neurons using neural networks not only avoids the manually seeking forthe optimal parameters, but also paves the way to build correspondingartificial versions for certain neurobiological organizations.

Low-Light Image Restoration Based on Retina Model using Neural Networks