A two-stage network for underwater image enhancement based on dual attention and multi-color space stretch

Jie Liu; Li Cao; He Deng; Yang Fu

doi:10.1117/12.3005493

7 March 2024 A two-stage network for underwater image enhancement based on dual attention and multi-color space stretch

Jie Liu, Li Cao, He Deng, Yang Fu

Proceedings Volume 13086, MIPPR 2023: Pattern Recognition and Computer Vision; 130860Q (2024) https://doi.org/10.1117/12.3005493
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China

Abstract

Underwater images can provide the underwater information intuitively and effectively. However, due to wavelength and distance related attenuation and scattering, underwater images may exhibit color distortion and low contrast. To address these two degradation issues, a novel two-stage network named as DAMcS-Net is proposed in this paper. In the first stage, a dual attention module that combines channel attention and spatial attention mechanisms is designed to amplify the network’s perception of detail textures. In the second stage, a multi-color space stretch module is designed to adaptively adjust the histogram distribution in RGB, HSI, and Lab color spaces, so that color projection and artifacts can be eliminated effectively. Quantitative and qualitative experiments show that our model has achieved state-of-the-art performance in comparison with existing methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jie Liu, Li Cao, He Deng, and Yang Fu "A two-stage network for underwater image enhancement based on dual attention and multi-color space stretch", Proc. SPIE 13086, MIPPR 2023: Pattern Recognition and Computer Vision, 130860Q (7 March 2024); https://doi.org/10.1117/12.3005493

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KEYWORDS

Image enhancement

RGB color model

Color

Education and training

Image quality

Histograms

Convolution

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