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

2022-10-04 08:14:49
Yurui Ming, Yuanyuan Liang
arXiv_AI
         
Abstract

We report the possibility of using a simple neural network for effortless restoration of low-light images inspired by the retina model, which mimics the neurophysiological principles and dynamics of various types of optical neurons. The proposed neural network model saves the cost of computational overhead in contrast with traditional signal-processing models, and generates results comparable with complicated deep learning models from the subjective perceptual perspective. This work shows that to directly simulate the functionalities of retinal neurons using neural networks not only avoids the manually seeking for the optimal parameters, but also paves the way to build corresponding artificial versions for certain neurobiological organizations.

Abstract (translated)

URL

https://arxiv.org/abs/2210.01806

PDF

https://arxiv.org/pdf/2210.01806.pdf

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