Optical Instruments, Volume. 46, Issue 5, 65(2024)

Low light image enhancement based on semantic information and attention mechanism

Haobin LI and Yunsong HUA*
Author Affiliations
  • School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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    References(15)

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    [10] [10] JIN X, XIAO J W, HAN L H, et al. Lighting every darkness in two pairs: a calibrationfree pipeline f RAW denoising[C]Proceedings of 2023 IEEECVF International Conference on Computer Vision. Paris: IEEE, 2023: 13229 − 13238.

    [11] [11] FU H Y, ZHENG W K, MENG X Y, et al. You do not need additional pris regularizers in retinexbased lowlight image enhancement[C]Proceedings of 2023 IEEECVF Conference on Computer Vision Pattern Recognition. Vancouver: IEEE, 2023: 18125 − 18134.

    [12] [12] BASLAMISLI A S, GROENESTEGE T T, DAS P, et al. Joint learning of intrinsic images semantic segmentation[C]Proceedings of the 15th European Conference on Computer Vision. Munich: Springer, 2018: 286 − 302.

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    [16] [16] ZHANG Y H, ZHANG J W, GUO X J. Kindling the darkness: a practical lowlight image enhancer[C]Proceedings of the 27th ACM International Conference on Multimedia. Nice: ACM, 2019: 1632 − 1640.

    [17] [17] LV F F, LU F, WU J H, et al. MBLLEN: lowlight imagevideo enhancement using CNNs[C]Proceedings of British Machine Vision Conference 2018. Newcastle: BMVA, 2018: 220.

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    Haobin LI, Yunsong HUA. Low light image enhancement based on semantic information and attention mechanism[J]. Optical Instruments, 2024, 46(5): 65

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    Paper Information

    Category:

    Received: Jul. 23, 2023

    Accepted: --

    Published Online: Jan. 3, 2025

    The Author Email: HUA Yunsong (hyuns_yz@163.com)

    DOI:10.3969/j.issn.1005-5630.202307230106

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