[1] Yuan Jijun. Review of infrared detector development[J]. Laser & Infrared, 36, 1099-1102(2006).

[2] [2] Liu Xinle. Research on fusion method of thermal infrared image visible light image[D]. Chengdu: University of Electronic Science Technology of China, 2013. (in Chinese)

[3] Zhang Shengwei, Xiang Wei, Zhao Yaohong. Stripe noise removal method for infrared images based on guided filtering[J]. Journal of Computer-Aided Design & Computer Graphics, 29, 1434-1443(2017).

[4] Cao Y P, Tisse C L. Single-image-based solution for optics temperature-dependent nonuniformity correction in an uncooled long wave infrared camera[J]. Optics Letters, 39, 646-648(2014).

[5] Chen Shihong, Chen Rongjun. Infrared image enhancement algorithm based on iteration deep convolution network[J]. Laser & Infrared, 51, 114-121(2021).

[6] Zhou Yi, Chai Xuliang, Tian Yuan, et al. Studies on InAs/GaAsSb mid-wavelength interband cascade infrared focal plane arrays[J]. Journal of Infrared and Millimeter Waves, 38, 745-750(2019).

[7] Liu Liping, Qiao Lele, Jiang Liucheng. Overview of image denoising methods[J]. Journal of Frontiers of Computer Science and Technolgy, 15, 1418-1431(2021).

[8] Tian Chunwei, Fei Lunke, Zheng Wenxian, et al. Deep learning on image denoising: An overview[J]. Neural Networks, 131, 251-275(2020).

[9] Liu B, Liu J. Overview of image denoising based on deep learning[J]. Journal of Physics: Conference Series, 1176, 022010(2019).

[10] Shizuo Kaji, Satoshi Kida. Overview of image to image translation by use of deep neural networks: Denoising, super-resolution, modality conversion, and reconstruction in medical imaging[J]. Radiological Physics and Technology, 12, 235-248(2019).

[11] Peng Zhenming, Chen Yingpin, Pu Tian. et al. Image denoising based on sparse representation and regularization constraint: A review[J]. Journal of Data Acquisition & Processing, 33, 1-11(2018).

[12] Liu Chengshi, Zhao Zhigang, Li Qiang, et al. Enhanced low-rank representation image denoising algorithm[J]. Computer En-gineering and Applications, 56, 216-225(2020).

[13] Wang Hongyu, Chen Dongmei, Wang Hui. Image denoising model based on low rank and nonlocal sparse representation[J]. Journal of Yanshan University, 272-277(2017).

[14] Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, et al. Image denoising by sparse 3D transform-domain collaborative filtering[J]. IEEE Transactions on Image Processing, 16, 2080-2095(2007).

[15] [15] Dabov K, Foi A, Katkovnik V, et al. Col image denoising via sparse 3D collabative filtering with grouping constraint in luminanccchrominance space[C]Processdings of the 2007 International Conference on Image Processing, 2007, 9: 313316.

[16] [16] Yaniv Romano, Michael Elad. Improving KSVD denoising by postprocessing its methodnoise[C]2013 IEEE International Conference on Image Processing, 2013.

[17] Zhang Kai, Zuo Wangmeng, Chen Yunjin, et al. Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 26, 3142-3155(2017).

[18] [18] Yu S, Park B, Jeong J. Deep iterative downup CNN f image denoising[C]Processings of the 2019 IEEE Conference on Computer Vision Pattern Recognition Wkshops, 2019, 7: 20952103.

[19] Liu Yichang, Ma Wei, Xu Shibiao. Edge-fidelity image denoising based on convolutional neural network[J]. Journal of Computer-Aided Design & Computer Graphics, 1822-1831(2020).

[20] Sun Haoze, Chang Tianqing, Zhang Lei, et al. Fast armored target detection based on lightweight network[J]. Journal of Computer-Aided Design & Computer Graphics, 1110-1121(2019).

[21] [21] Chen Jingwen, Chen Jiawei, Chao Hongyang. et al. Image blind denoising with generative adversarial wk based noise modeling[C]2018 IEEECVF Conference on Computer Vision Pattern Recognition, 2018, 7: 31553164.

[22] [22] Zhang Kai, Zuo Wangmeng, Zhang Lei. et al. Learning a single convolutional superresolution wk f multiple degradations[C]2018 IEEECVF Conference on Computer Vision Pattern Recognition, 2018,

[23] Itti Laurent, Christof Koch. Computational modelling of visual attention[J]. Nature Reviews Neuroscience, 2, 194-203(2001).

[24] [24] Li Xiang, Wang Wenhai, Hu Xiaolin. et al. ive kernel wks[C]CVPR2019, 2019.

[25] He Kaiming, Sun Jian, Tang Xiaoou. Guided image filtering[J]. IEEE Transactions on Software Engineering, 35, 1397-1409(2013).

[26] [26] Zhu Xizhou, Cheng Dazhi, Zhang Zheng, et al. An empirical study of spatial attention mechanisms in deep wks[C]ICCV2019, 2019.

[27] [27] Zhang Yulun, Li Kunpeng, Li Kai. et al. Image superresolution using very deep residual channel attention wks[C]ECCV2018, 2018: 294310.

[28] [28] Chen Long, Zhang Hanwang, Xiao Jun, et al. SCACNN: Spatial channelwise attention in convolutional wks f image captioning[C]CVPR, 2017.

[29] He Kaiming, Sun Jian, Tang Xiaoou. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33, 2341-2353(2011).

[30] [30] He Kaiming, Zhang Xiangyu, Ren Shaoqing, et al. Deep residual learning f image recognition[C]CVPR, 2016.

[31] Chen Liang Chieh, George Papandreou, lasonas Kokkinos, et al. DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 834-848(2018).

[32] Wang Zhou, Bovik A C, Sheikh H R, et al. Image quality assessment: From error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 13, 600-612(2004).

[33] Wang Zhou, Li Qiang. Information content weighting for perceptual image quality assessment[J]. IEEE Tansactions on Image Processing, 20, 1185-1198(2011).

[34] [34] Guo Shi, Yan Zifei, Zhang Kai, et al. Toward convolutional blind denoising of real photographs[C]CVPR, 2019.

[35] [35] Zamir S W, Ara A, Khan S H, et al. Learning enriched feature f real image restation enhancement[C]ECCV, 2020: 492511.

[36] [36] Saeed Anwar, Nick Barnes. Real image denoising with feature attention[C]IEEECVF International Conference on Comptuer Vision (ICCV), 2019.

[37] Zhang Kai, Li Yawei, Zuo Wangmeng, et al. Plug-and-play image restoration with deep denoiser prior[J]. IEEE Transcations on Pattern Analysis and Machine Intelligence, 44, 6360-6376(2021).