[1] Liang C P, Feng Y D, Xie H R et al. Prior-based single image rain and haze removal[J]. Journal of Zhejiang University (Science Edition), 48, 270-281, 288(2021).

[2] Xie Y H, Xie Y, Chen L et al. Object detection in real-world hazy scene[J]. Journal of Computer-Aided Design & Computer Graphics, 33, 733-745(2021).

[3] Zhang Y F, Li Y X, Zhao M B et al. Object distance estimation based on stereo regional disparity regression[J]. Journal of Image and Graphics, 26, 1604-1613(2021).

[4] Jin D F, Chen F, Peng Z J et al. Preprocessing based depth video fast intra coding algorithm[J]. Journal of Optoelectronics·Laser, 28, 1131-1138(2017).

[5] Huo Z Y, Qiao L. Research on monocular depth estimation algorithm based on structured loss[J]. Journal of University of Electronic Science and Technology of China, 50, 728-733(2021).

[6] Dong J K, Liu K, Wang J N. Simulation of the foggy scene under outdoor natural scenes[J]. Journal of Computer-Aided Design & Computer Graphics, 25, 397-401, 409(2013).

[7] Sakaridis C, Dai D X, Van Gool L. Semantic foggy scene understanding with synthetic data[J]. International Journal of Computer Vision, 126, 973-992(2018).

[8] Hahner M, Dai D X, Sakaridis C et al. Semantic understanding of foggy scenes with purely synthetic data[C], 3675-3681(2019).

[9] Song H S, Liu Y P, Zheng H L et al. Road visibility detection based on priori theory of dark and bright primary colors[J]. Laser＆Optoelectronics Progress, 58, 0601001(2021).

[10] Nayar S K, Narasimhan S G. Vision in bad weather[C], 820-827(1999).

[11] Godard C, Aodha O M, Firman M et al. Digging into self-supervised monocular depth estimation[C], 3827-3837(2019).

[12] Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation[EB/OL]. https://arxiv.org/abs/1505.04597

[13] Zhou T H, Brown M, Snavely N et al. Unsupervised learning of depth and ego-motion from video[C], 6612-6619(2017).

[14] Mayer N, Ilg E, Häusser P et al. A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation[C], 4040-4048(2016).

[15] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

[16] Qin Z, Yang J G, Wang H M et al. Low illumination transmission line image enhancement method and application based on the Retinex theory[J]. Power System Protection and Control, 49, 150-157(2021).

[17] Li M R, Liu X M, Chang J. An adaptive retinex of image haze removal based on color attenuation prior[J]. Computer Simulation, 38, 354-358(2021).

[18] Li S T, Kang X D, Hu J W. Image fusion with guided filtering[J]. IEEE Transactions on Image Processing, 22, 2864-2875(2013).

[19] Hautiére N, Tarel J P, Lavenant J et al. Automatic fog detection and estimation of visibility distance through use of an onboard camera[J]. Machine Vision and Applications, 17, 8-20(2006).

[20] Wang J, Liu Y Y, Zhang X W et al. Summary of atmospheric light value estimation methods in haze images[J]. Laser Journal, 42, 6-10(2021).

[21] Yang Y, Lu X X. An image dehazing method combining adaptive brightness transformation inequality to estimate transmittance[J]. Journal of Xi’an Jiaotong University, 55, 69-76(2021).

[22] Yu M J, Zhang H F. Single-image dehazing based on dark channel and incident light assumption[J]. Journal of Image and Graphics, 19, 1812-1819(2014).

[23] He K M, Sun J, Tang X O. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33, 2341-2353(2011).

[24] Guo T Y, Li N, Sun L L et al. A defogging method containing images of sky regions[J]. Laser & Optoelectronics Progress, 59, 0210009(2022).

[25] Mittal A, Moorthy A K, Bovik A C. No-reference image quality assessment in the spatial domain[J]. IEEE Transactions on Image Processing, 21, 4695-4708(2012).

[26] Mittal A, Soundararajan R, Bovik A C. Making a “completely blind” image quality analyzer[J]. IEEE Signal Processing Letters, 20, 209-212(2013).

[27] Venkatanath N, Praneeth D, Bh M C et al. Blind image quality evaluation using perception based features[C](2015).

[28] Yao Y, Abidi B, Doggaz N et al. Evaluation of sharpness measures and search algorithms for the auto-focusing of high-magnification images[J]. Proceedings of SPIE, 6246, 62460G(2006).

[29] Li Y F, Chen N N, Zhang J C. Fast and high sensitivity focusing evaluation function[J]. Application Research of Computers, 27, 1534-1536(2010).