Underwater image enhancement based on conditional generative adversarial network

Underwater images play an essential role in acquiring and understanding underwater information. High-quality underwater images can guarantee the reliability of underwater intelligent systems. Unfortunately, underwater images are characterized by low contrast, color casts, blurring, low light, and un...

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Vydáno v:	Signal processing. Image communication Ročník 81; s. 115723
Hlavní autoři:	Yang, Miao, Hu, Ke, Du, Yixiang, Wei, Zhiqiang, Sheng, Zhibin, Hu, Jintong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 01.02.2020 Elsevier BV
Témata:	Adversarial learning Blurring Conditional generative adversarial networks Deep learning Generative adversarial networks Image acquisition Image contrast Image enhancement Image quality Machine learning Underwater Underwater image enhancement Deep learning Underwater image enhancement Conditional generative adversarial networks Adversarial learning
ISSN:	0923-5965, 1879-2677
On-line přístup:	Získat plný text
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