Low-Light Image Restoration Based on Retina Model using Neural Networks
- URL: http://arxiv.org/abs/2210.01806v1
- Date: Tue, 4 Oct 2022 08:14:49 GMT
- Title: Low-Light Image Restoration Based on Retina Model using Neural Networks
- Authors: Yurui Ming and Yuanyuan Liang
- Abstract summary: 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 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.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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