[1] Huang Hong, Tang Yuxiao, Duan Yule. Feature extraction of hyperspectral image with semi-supervised multi-graph embedding[J]. Optics and Precision Engineering, 2020, 28(2):443-456. (in Chinese)黄鸿, 唐玉枭, 段宇乐. 半监督多图嵌入的高光谱影像特征提取[J]. 光学精密工程, 2020, 28(2):443-456.
[2] Zhao Huijie, Li Jimin, Jia Guorui, et al. Correlation-wavelet method for separation of hyperspectral thermal infrared temperature and emissivity[J]. Optics and Precision Engineering, 2019, 27(8):1738-1744. (in Chinese)赵慧洁, 李济民, 贾国瑞, 等. 高光谱热红外温度发射率分离的相关小波法[J]. 光学精密工程, 2019, 27(8):1738-1744.
[3] He Sailing, Chen Xiang, Li Shuo, et al. Small hyperspectral imagers and lidars and their marine applications[J]. Infrared and Laser Engineering, 2020, 49(2):0203001. (in Chinese)何赛灵, 陈祥, 李硕, 等. 小型高光谱图谱仪与激光雷达及其海洋应用[J].红外与激光工程, 2020, 49(2):0203001.
[4] Arad B, Benshahar O. Sparse recovery of hyperspectral signal from natural RGB images[C]//European Conference on Computer Vision, 2016:19-34.
[5] Zhang Zexia, Chang Jun, Ren Hongxi, et al. Snapshot imaging spectrometer based on a microlens array[J]. Chinese Optics Letters, 2019, 17(1):35-39.
[6] Takatani T, Aoto T, Mukaigawa Y, et al. One-shot hyperspectral imaging using faced reflectors[C]//Computer Vision and Pattern Recognition, 2017:2692-2700.
[7] Oh S W, Brown M S, Pollefeys M, et al. Do it yourself hyperspectral imaging with everyday digital cameras[C]//Computer Vision and Pattern Recognition, 2016:2461-2469.
[8] Akhtar N, Shafait F, Mian A, et al. Hierarchical beta Process with gaussian process prior for hyperspectral image super resolution[C]//European Conference on Computer Vision, 2016:103-120.
[9] Jia Y, Zheng Y, Gu L, et al. From RGB to spectrum for natural scenes via manifold-based mapping[C]//International Conference on Computer Vision, 2017:4715-4723.
[10] Wang Chunzhe, An Junshe, Jiang Xiujie, et al. Region proposal optimization algorithm based on convolutional neural networks[J]. Chinese Optics, 2019, 12(6):1348-1361. (in Chinese)王春哲, 安军社, 姜秀杰, 等. 基于卷积神经网络的候选区域优化算法[J]. 中国光学, 2019, 12(6):1348-1361.
[11] Zhang Lamei, Chen Zexi, Zou Bin. Fine classification of polarimetric SAR images based on 3D convolutional neural network[J]. Infrared and Laser Engineering, 2018, 47(7):0703001. (in Chinese)张腊梅, 陈泽茜, 邹斌. 基于3D卷积神经网络的PolSAR图像精细分类[J]. 红外与激光工程, 2018, 47(7):0703001.
[12] Zhang Xiu, Zhou Wei, Duan Zhemin, et al. Convolutional sparse auto-encoder for image super-resolution reconstruction[J]. Infrared and Laser Engineering, 2019, 48(1):0126005. (in Chinese)张秀, 周巍, 段哲民, 等. 基于卷积稀疏自编码的图像超分辨率重建[J].红外与激光工程, 2019, 48(1):0126005.
[13] Xiong Z, Shi Z, Li H, et al. HSCNN:CNN-based hyperspectral image recovery fromspectrally undersampled projections[C]//International Conference on Computer Vision, 2017:518-525.
[14] Shi Z, Chen C, Xiong Z, et al. HSCNN+:advanced CNN-based hyperspectral recovery from RGB images[C]//Computer Vision and Pattern Recognition, 2018:939-947.
[15] Alvarezgila A, De Weijer J V, Garrote E, et al. Adversarial networks for spatial context-aware spectral image reconstruction from RGB[C]//International Conference on Computer Vision, 2017:480-490.
[16] Chakrabarti A, Zickler T. Statistics of real-world hyperspectral images[C]//Computer Vision and Pattern Recognition, 2011:193-200.