[5] [5] LI X, ZHANG H. An improved canny edge detection algithm[C]Proceedings of the 2017 8th IEEE International Conference on Software Engineering Service Science (ICSESS). Beijing: IEEE, 2017: 577−582.

[6] [6] HE K M, SUN J, TANG X O. Single image haze removal using dark channel pri[C]Proceedings of 2009 IEEE Conference on Computer Vision Pattern Recognition. Miami: IEEE, 2009: 2341−2353.

[7] [7] DONG X, WANG G, PANG Y, et al. Fast efficient algithm f enhancement of low lighting video[C]Proceedings of 2011 IEEE International Conference on Multimedia Expo. Barcelona: IEEE, 2011: 16.

[9] ZHOU Y Q, XIE L S Q, HE K J et al. Low-light image enhancement for infrared and visible image fusion[J]. IET Image Processing, 17, 3216-3234(2023).

[10] [10] CHEN C, CHEN Q F, XU J, et al. Learning to see in the dark[C]Proceedings of 2018 IEEECVF Conference on Computer Vision Pattern Recognition. Salt Lake City: IEEE, 2018: 3291−3300.

[11] LI C Y, GUO J C, PORIKLI F et al. LightenNet: a convolutional neural network for weakly illuminated image enhancement[J]. Pattern Recognition Letters, 104, 15-22(2018).

[12] [12] 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.

[13] [13] WU W H, WENG J, ZHANG P P, et al. URetinex: Retinexbased deep unfolding wk f lowlight image enhancement[C]Proceedings of IEEECVF Conference on Computer Vision Pattern Recognition. New leans: IEEE, 2022: 5901−5910.

[14] JIANG Y F, GONG X Y, LIU D et al. EnlightenGAN: deep light enhancement without paired supervision[J]. IEEE transactions on image processing, 30, 2340-2349(2021).

[15] [15] MA L, MA T Y, LIU R S, et al. Toward fast, flexible, robust lowlight image enhancement[C]Proceedings of the IEEECVF conference on computer vision pattern recognition. New leans: IEEE, 2022: 5637−5646.

[16] [16] LIU R S, MA L, ZHANG J A, et al. Retinexinspired unrolling with cooperative pri architecture search f lowlight image enhancement[C]Proceedings of IEEECVF Conference on Computer Vision Pattern Recognition. Nashville: IEEE, 2021: 10561−10570.

[17] WANG Q T, CHEN W H, WU X M et al. Detail-enhanced multi-scale exposure fusion in YUV color space[J]. IEEE Transactions on Circuits and Systems for Video Technology, 30, 2418-2429(2020).

[18] MITTAL A, SOUNDARARAJAN R, BOVIK A C. Making a "completely blind" image quality analyzer[J]. IEEE Signal Processing Letters, 20, 209-212(2013).

[20] LORE K G, AKINTAYO A, SARKAR S. LLNet: a deep autoencoder approach to natural low-light image enhancement[J]. Pattern Recognition, 61, 650-662(2017).

[21] LI C Y, GUO C L, CHEN C L. Learning to enhance low-light image via zero-reference deep curve estimation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 4225-4238(2022).