GACA: A Gradient-Aware and Contrastive-Adaptive Learning Framework for Low-Light Image Enhancement

Image gradients contain crucial information in the images. However, the gradient information of low-light images is often concealed in darkness and is susceptible to noise contamination. This imprecise gradient information poses a significant obstacle to low-light image enhancement (LLIE) tasks. Sim...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement 2024, Vol.73, p.1-14
Hauptverfasser:	Yao, Zishu, Su, Jian-Nan, Fan, Guodong, Gan, Min, Chen, C. L. Philip
Format:	Artikel
Sprache:	eng
Schlagworte:	Abnormalities Benchmarks Darkness Datasets Image enhancement Image processing Image quality Image reconstruction Image restoration Learning Mapping Regularization
Online-Zugang:	Volltext
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