Learning a Single Convolutional Layer Model for Low Light Image Enhancement

Low-light image enhancement (LLIE) aims to improve the illuminance of images due to insufficient light exposure. Recently, various lightweight learning-based LLIE methods have been proposed to handle the challenges of unfavorable prevailing low contrast, low brightness, etc. In this paper, we have s...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology 2024-07, Vol.34 (7), p.5995-6008
Hauptverfasser:	Zhang, Yuantong, Teng, Baoxin, Yang, Daiqin, Chen, Zhenzhong, Ma, Haichuan, Li, Gang, Ding, Wenpeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Computational modeling convolutional layer Convolutional neural networks Deep learning Effectiveness Illuminance Image enhancement Learning Lighting Low-light image enhancement Parameter estimation Parameterization Parameters structural re-parameterization Training Visual effects
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