Underwater Image Enhancement With a Deep Residual Framework

Underwater Image Enhancement With a Deep Residual Framework

Owing to refraction, absorption, and scattering of light by suspended particles in water, raw underwater images have low contrast, blurred details, and color distortion. These characteristics can significantly interfere with visual tasks, such as segmentation and tracking. This paper proposes an und...

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Bibliographic Details
Main Authors: Peng Liu, Guoyu Wang, Hao Qi, Chufeng Zhang, Haiyong Zheng, Zhibin Yu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Asynchronous training
edge difference loss
residual learning
underwater image enhancement
Online Access:https://ieeexplore.ieee.org/document/8763933/

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