Comparison of GAN Deep Learning Methods for Underwater Optical Image Enhancement

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwat...

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Bibliographic Details

Published in:	Han-guk haeyang gonghak hoeji (Online) Vol. 36; no. 1; pp. 32 - 40
Main Authors:	Kim, Hong-Gi, Seo, Jung-Min, Kim, Soo Mee
Format:	Journal Article
Language:	English
Published:	한국해양공학회 01-02-2022 The Korean Society of Ocean Engineers
Subjects:	generative adversarial networks image enhancement image fusion underwater image deep learning techniques underwater optical image 해양공학 Generative adversarial networks Underwater optical image Underwater image deep learning techniques Image fusion Image enhancement
Online Access:	Get full text
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