[1] P GHAMISI, N YOKOYA, Jun LI et al. Advances in hyperspectral image and signal processing: a comprehensive overview of the state of the art. IEEE Geoscience and Remote Sensing Magazine, 5, 37-78(2017).
[2] Chengye ZHANG, Qiming QIN, Li CHEN等. Research and development of mineral identification utilizing hyperspectral remote sensing. Optics and Precision Engineering, 23, 2407-2418(2015).
[3] Zhongqi TANG, Guangyuan FU, Jin CHEN等. Multiscale segmentation based sparse coding for hyperspectral image classification. Optics and Precision Engineering, 23, 2708-2714(2015).
[4] Wei LI, Fubiao FENG, Hengchao LI et al. Discriminant analysis-based dimension reduction for hyperspectral image Classification: a survey of the most recent advances and an experimental comparison of different techniques. IEEE Geoscience and Remote Sensing Magazine, 6, 15-34(2018).
[5] Weiwei SUN, Gang YANG, Bo DU et al. A sparse and low-Rank near-Isometric linear embedding method for feature extraction in hyperspectral imagery classification. IEEE Transactions on Geoscience and Remote Sensing, 55, 4032-4046(2017).
[6] Yuhang GAN, Fulin LUO, Juhua LIU et al. Feature extraction based multi-structure manifold embedding for hyperspectral remote sensing image classification. PP: 25069, 25080(2017).
[7] Xuemei CHENG, Yuren CHEN, Yang TAO et al. A novel integrated PCA and FLD method on hyperspectral image feature extraction for cucumber chilling damage inspection. Transactions of the ASAE, 47, 1313-1320(2004).
[8] Lixin GUAN, Weixin XIE, Jihong PEI. Segmented minimum noise fraction transformation for efficient feature extraction of hyperspectral images. Pattern Recognition, 48, 3216-3226(2015).
[9] Xiaofei HE, P NIYOGI. Locality preserving projection. Neural Information Processing Systems, 153-160(2004).
[10] Xiaofei HE, Deng CAI, Shuicheng YAN et al. Neighborhood preserving embedding. IEEE International Conference on Computer Vision, 1208-1213(2005).
[11] Xingzhong DU, Yan YAN, Pingbo PAN et al. Multiple graph unsupervised feature selection. Signal Processing, 754-760(2016).
[12] Yi YANG, Dong XU, Feiping NIE et al. Image clustering using local discriminant models and global integration. IEEE Transactions on Image Processing, 19, 2761-2773(2010).
[13] Lishan QIAO, Songcan CHEN, Xiaoyang TAN. Sparsity preserving projections with applications to face recognition. Pattern Recognition, 43, 331-341(2010).
[14] Fulin LUO, Hong HUANG, Jiamin LIU et al. Fusion of graph embedding and sparse representation for feature extraction and classification of hyperspectral imagery. Photogrammetric Engineering and Remote Sensing, 83, 37-46(2017).
[15] Yuanyan TANG, Haoliang YUAN, Luoqing LI. Manifold-based sparse representation for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 52, 7606-7618(2014).
[16] Yule DUAN, Hong HUANG, Zhengying LI et al. Local Manifold-based sparse discriminant learning for feature extraction of hyperspectral image. PP:1, 14(2020).
[17] D CALVETTI, L REICHEL. Application of ADI iterative methods to the restoration of noisy images. SIAM Journal on Matrix Analysis and Applications, 17, 165-186(1996).
[18] Hong HUANG, Guangyao SHI, Haibo HE et al. Dimensionality reduction of hyperspectral imagery based on spatial-spectral manifold learning. IEEE Transactions on Cybernetics, 50, 2604-2616(2020).