A lightweight stacked residual low-light image enhancement network for USV optical vision perception&nbsp;

LIU Ting, ZHANG Yuxin, WANG Guofeng, LUO Peiqi, FAN Yunsheng

doi:10.16411/j.cnki.issn1006-7736.2024.02.006

Journal of Dalian Maritime University >

2024 , Vol. 50 >Issue 2: 53 - 66

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2024.02.006

A lightweight stacked residual low-light image enhancement network for USV optical vision perception

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(College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China)

Online published: 2023-11-28

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Abstract

A lightweight stacked residual low-light image enhancement network is proposed to overcome the difficulty in accurately sensing the environment under low-light conditions for Unmanned surface vessels (USV). Firstly, a pyramid multi-scale pooling is introduced into feature fusion to better preserve image details. Secondly, depthwise separable convolution is introduced to lighten the network and improve the image processing speed. Thirdly, a new composite loss function with color loss is designed to reduce color distortion. Finally, LeakyReLU activation function is used to prevent neuronal death. Results from extensive experiments demonstrate that our method can effectively improve image quality while speeding up image processing compared to Stacked Attention Residual Network (SARN). Specifically, SSIM (Structure Similarity Index Measure) and PSNR (Peak Signal-to-Noise Ratio) are improved by 3.31% and 2.08% and FLOPs (Floating point operations), params and processing time of single image are reduced by 81.88%, 75% and 43.02%. Therefore, the proposed method is suitable for low-light image enhancement of USV, and has certain application value.

Key words： low-light image enhancement; convolutional neural network; depthwise separable convolution; Pyramid pooling; color loss

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LIU Ting, ZHANG Yuxin, WANG Guofeng, LUO Peiqi, FAN Yunsheng . A lightweight stacked residual low-light image enhancement network for USV optical vision perception [J]. Journal of Dalian Maritime University, 2024 , 50(2) : 53 -66 . DOI: 10.16411/j.cnki.issn1006-7736.2024.02.006

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