Benchmarking Low-Light Image Enhancement and Beyond

In this paper, we present a systematic review and evaluation of existing single-image low-light enhancement algorithms. Besides the commonly used low-level vision oriented evaluations, we additionally consider measuring machine vision performance in the low-light condition via face detection task to...

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Veröffentlicht in:	International journal of computer vision Jg. 129; H. 4; S. 1153 - 1184
Hauptverfasser:	Liu, Jiaying, Xu, Dejia, Yang, Wenhan, Fan, Minhao, Huang, Haofeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2021 Springer Springer Nature B.V
Schlagworte:	Algorithms Annotations Artificial Intelligence Benchmarks Computer Imaging Computer Science Datasets Detectors Face recognition Feature extraction Image enhancement Image Processing and Computer Vision Light Machine vision Modules Optimization Pattern Recognition Pattern Recognition and Graphics Special Issue on Computer Vision for All Seasons: Adverse Weather and Lighting Conditions Vision Benchmark Face detection Dataset Low-light enhancement
ISSN:	0920-5691, 1573-1405
Online-Zugang:	Volltext
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