About the Editor xxi List of Contributors xxiii 1 Review for Machine-Learning-Based Hyperspectral Image Analysis 1 He Sun and Ruitong Du 1.1 Overview 1 1.2 Denoising 2 1.3 Super-resolution 4 1.4 Unmixing 7 1.5 Classification 8 1.6 Target Detection 11 1.7 Change Detection 13 1.

8 Experimental Datasets 15 1.9 Chapter Arrangement and Writing Purpose 19 2 Hyperspectral Image Denoising Based on Low-rank Regularization 31 Yong Chen, Hongyu Chen, and Wei He 2.1 Introduction 31 2.2 Model-driven Approaches 32 2.3 Data-driven Approaches 41 2.4 Conclusion and Outlook 46 3 Hyperspectral Image Denoising Based on Tensor Models 51 Yu-Bang Zheng, Jian-Li Wang, and Xi-Le Zhao 3.1 Introduction 51 3.2 HSI Reconstruction 52 3.

3 Tensor Modeling-based HSI Reconstruction Methods 53 3.4 Numerical Experiments 66 3.5 Conclusion 67 4 Hyperspectral Image Denoising Based on Spatial-Spectral Joint Constraints 73 Bin Zhao, Magnus O. Ulfarsson, Jakob Sigurdsson, Jon Atli Benediktsson, and Jocelyn Chanussot 4.1 Non-local Means Low-rank Approximation 73 4.2 Wavelet-based Block Low-rank Representations 79 4.3 Conclusions 84 5 Hyperspectral Image Reconstruction Based on Spectral Super-resolution 87 Prof. Yanfeng Gu 5.

1 Introduction 87 5.2 Experimental Datasets and Evaluation Indicators 90 5.3 A Learning Subpixel Super-resolution Model Based on Coupled Dictionary 95 5.4 A Collaborative Spectral-super-resolution Model Based on Adaptive Learning 106 5.5 Conclusion 124 6 Hyperspectral Image Reconstruction From Supervision to Blindness 129 Jie Xie, Jie Wu, Zhicheng Wang, Lina Zhuang, and Leyuan Fang 6.1 Introduction 129 6.2 Full Supervised HSI SR 132 6.3 Weakly Supervised HSI SR 137 6.

4 Self-supervised HSI SR 153 6.5 Blind HSI SR 169 6.6 Conclusion and Discussion 181 7 Hyperspectral Image Reconstruction Based on Unsupervised Learning 191 Ying Qu, Jiangsan Zhao, Hairong Qi, Chiman Kwan, and Liqiang Zhang 7.1 Introduction 191 7.2 Problem Formulation 193 7.3 Unsupervised Hyperspectral Image Super-resolution with Dirichlet Net 193 7.4 Unsupervised and Unregistered Hyperspectral Image Super-resolution 196 7.5 Improving SR Performance with Endmember-assisted Camera Response Function Learning 200 7.

6 Conclusions 201 8 Hyperspectral Image Reconstruction Based on Adaptive Learning 207 Ke Zheng, Jiaxin Li, Lianru Gao, and Bing Zhang 8.1 Introduction 207 8.2 Problem Formulation 208 8.3 Numerical Model-guided Nonlinear Spectral Unmixing 209 8.4 Experiment and Results 218 8.5 Conclusion 227 9 Hyperspectral Unmixing with Nonnegative Matrix Factorization 229 Jun Li, Yuanchao Su, Shaoquan Zhang, and Ruoqing Xu 9.1 Introduction 229 9.2 Methodologies 230 9.

3 Experiments 235 9.4 Conclusion 239 10 Hyperspectral Unmixing Based on Low-rank Representation and Sparse Constraint 243 Xiangrong Zhang, Jingyan Zhang, Guanchun Wang, and Licheng Jiao 10.1 Introduction 243 10.2 Linear Unmixing Algorithms 244 10.3 Hybrid Unmixing Algorithms 251 10.4 Experiments 257 10.5 Conclusions 266 11 Endmember Purification and Geographical Knowledge Graph-guided Endmember Selection 271 Wenfei Luo and Rui Wu 11.1 Introduction 271 11.

2 Endmember Purification 272 11.3 Unmixing with Geographic Knowledge Graph 283 11.4 Experimental Results and Analysis 289 11.5 Conclusion 298 12 Hyperspectral Unmixing Based on Deep Autoencoder Networks 301 Yuanchao Su, Jun Li, Lianru Gao, Ruoqing Xu, Zhiqing Zhu, and Paolo Gamba 12.1 Introduction 301 12.2 Methodologies 302 12.3 Experimental Results 314 12.4 Conclusion 318 12.

5 Discussion 318 13 Numerical-model-guided Nonlinear Spectral Unmixing 321 Bin Yang and Bin Wang 13.1 Introduction 321 13.2 Nonlinear Mixture Models and Extensions 324 13.3 Numerical-model-guided Nonlinear Spectral Unmixing 327 13.4 Conclusions 344 13.5 Challenges and Future Directions 346 14 Spatial-Spectral Gabor-based Hyperspectral Image Classification 351 Sen Jia, Shuyu Zhang, Qi Ren, Wangquan He, Meng Xu, and Jiasong Zhu 14.1 Spatial-Spectral Gabor Feature Extraction 351 14.2 Pixel-wise Gabor Features for Hyperspectral Image Classification 359 14.

3 Superpixel-wise Gabor Features for HSI Classification 372 15 Domain Adaptation for Hyperspectral Image Classification 389 Chong Li, Weiwei Sun, Jiangtao Peng, and Kai Ren 15.1 Basic Concepts of Domain Adaptation 389 15.2 Domain Adaptation for Hyperspectral Image Classification 390 15.3 Deep Domain-adaptation-based Hyperspectral Image Classification 391 15.4 Conclusion 402 16 Unsupervised Domain Adaptation for Classification of Hyperspectral Images 405 li Ma and Qian Du 16.1 Introduction 405 16.2 Unsupervised Domain Adaptation Problem 408 16.3 Traditional Unsupervised Domain Adaptation Methods 408 16.

4 Deep-learning-based Unsupervised Domain Adaptation Methods 411 16.5 Experimental Results and Analysis 414 16.6 Conclusions 420 17 Lightweight Models for Hyperspectral Image Classification 425 Hongmin Gao, Shufang Xu, Zhonghao Chen, and Yiyan Zhang 17.1 Introduction 425 17.2 Lightweight Feature Extraction-based Hyperspectral Image Classification 427 17.3 Experimental Results and Analysis 438 17.4 Conclusion 446 18 Ensemble Method Based Hyperspectral Image Classification 453 Wei Feng and Mengdao Xing 18.1 Background 453 18.

2 Introduction to Ensemble Learning 454 18.3 Ensemble Learning in HSI Classification 459 18.4 Conclusion 467 19 Spectral-Spatial Hyperspectral Image Classification Based on Sparse Representation 471 Haoyang Yu, Jia Jia, Chuhan Shen, Jiaochan Hu, Chein-I Chang, and Lianru Gao 19.1 Introduction 471 19.2 Related Models Description 472 19.3 Hyperspectral Image Classification Based on Sparse Representation 475 19.4 Experimental Results and Analysis 485 19.5 Conclusion 495 20 Hyperspectral Image Classification with Limited Samples 499 Yuebin Wang, Liqiang Zhang, Bing Zhang, Antonio Plaza, and Xiao Xiang Zhu 20.

1 Introduction 499 20.2 Method 503 20.3 Experimental Results 509 20.4 Conclusions 519 21 Constrained Energy Minimization Based Hyperspectral Image Target Detection 521 Zhenwei Shi, Zhengxia Zou, Bowen Chen, and Liqin Liu 21.1 Introduction 521 21.2 Overview of CEM 522 21.3 CEM-based Methods 525 21.4 Conclusions 539 22 Hyperspectral Target Detection Based on Weighted Cauchy Distance Graph and Local Adaptive Collaborative Representation 543 Wei Li and Kun Gao 22.

1 Introduction 543 22.2 Related Works 545 22.3 The Proposed Detection Methodology 546 22.4 Experiments and Analysis 551 22.5 Conclusion 558 23 Weakly Supervised Learning-based Hyperspectral Image Anomaly/Target Detection 561 Weiying Xie, Xin Zhang, Yunsong Li, and Qian Du 23.1 Introduction 561 23.2 Weakly Supervised Hyperspectral Anomaly Detection (WSLRR) 564 23.3 Weakly Supervised Hyperspectral Target Detection (BLTSC) 573 23.

4 Rank-aware Hyperspectral Band Selection (R-GAN) 578 23.5 Conclusions 587 24 Hyperspectral Anomaly Detection via Background-separable Mode 593 Bing Tu, Xianchang Yang, Jun Li, Antonio Plaza, and Kaiyuan Chen 24.1 Hyperspectral Anomaly Detection Using Dual Window Density 593 24.2 Hyperspectral Anomaly Detection Using Reconstruction Fusion of Quaternion Frequency Domain Analysis 603 24.3 Ensemble Entropy Metric for Hyperspectral Anomaly Detection 619 25 Spectral Change Analysis for Multitemporal Change Detection in Hyperspectral Remote Sensing Images 633 Sicong Liu, Kecheng Du, Xiaohua Tong, and Peijun Du 25.1 Introduction 633 25.2 Related Works 635 25.3 Spectral Change Analysis in Hyperspectral Images 637 25.

4 Experimental Setup 643 25.5 Results and Analysis 643 25.6 Conclusion 650 Acknowledgement 650 26 Challenges and Future Directions 655 Bing Zhang, He Sun, and Ruitong Du 26.1 Challenges and Future Directions in Hyperspectral Image Denoising 655 26.2 Challenges and Future Directions in Hyperspectral (HS) and Multispectral (MS) Image Fusion 657 26.3 Challenges and Future Directions in NMF-based Hyperspectral Unmixing 659 26.4 Challenges and Future Directions in Knowledge Graph-enhanced Hyperspectral Unmixing 660 26.5 Challenges and Future Directions in Numerical Model-guided Nonlinear Hyperspectral Unmixing 660 26.

6 Challenges and Future Directions in Hyperspectral Image Classification 661 26.7 Chapter on Challenges and Future Directions in Hyperspectral Target Detection 662 References 663 Index 665.