Bio-Inspired Simple Neural Network for Low-Light Image Restoration: A Minimalist Approach

Junjie Ye; Jilin Zhao

doi:10.20944/preprints202305.0067.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 1 May 2023 / Approved: 2 May 2023 / Online: 2 May 2023 (07:32:56 CEST)

In this study, we explore the potential of using a straightforward neural network inspired by the retina model to efficiently restore low-light images. The retina model imitates the neurophysiological principles and dynamics of various optical neurons. Our proposed neural network model reduces the computational overhead compared to traditional signal-processing models while achieving results similar to complex deep learning models from a subjective perceptual perspective. By directly simulating retinal neuron functionalities with neural networks, we not only avoid manual parameter optimization but also lay the groundwork for constructing artificial versions of specific neurobiological organizations.

low light; image enhancement; counvolutional neural networks

Computer Science and Mathematics, Computer Vision and Graphics

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Bio-Inspired Simple Neural Network for Low-Light Image Restoration: A Minimalist Approach

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