Dual-GAN Complementary Learning for Real-World Image Denoising

The imaging process of real-world images is inevitably polluted by noise, which affects the visual quality and subsequent processing of images. How to restore image details while removing noise has always been a challenging problem. The existing complementary learning strategies combine the advantag...

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Veröffentlicht in:	IEEE sensors journal 2024-01, Vol.24 (1), p.355-366
Hauptverfasser:	Zhao, Shaobo, Lin, Sheng, Cheng, Xi, Zhou, Kexue, Zhang, Min, Wang, Hai
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Complementary learning Datasets deep learning generative adversarial network (GAN) Generative adversarial networks Generators Image denoising Image quality Image restoration Noise measurement Noise reduction Performance enhancement Sensors Training
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