Fast Underwater Image Enhancement for Improved Visual Perception

In this letter, we present a conditional generative adversarial network-based model for real-time underwater image enhancement. To supervise the adversarial training, we formulate an objective function that evaluates the perceptual image quality based on its global content, color, local texture, and...

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Bibliographic Details
Published in:	IEEE robotics and automation letters Vol. 5; no. 2; pp. 3226 - 3233
Main Authors:	Islam, Md Jahidul, Xia, Youya, Sattar, Junaed
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	computer vision for automation deep learning in robotics and automation Gallium nitride Generators Image detection Image enhancement Image quality Marine robotics Object recognition Optical distortion Performance enhancement Real time Real-time systems Training Underwater robots Visibility Visual perception
ISSN:	2377-3766, 2377-3766
Online Access:	Get full text
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