Advances in Hyperspectral Image Processing Techniques

Chein-I Chang, PhD, is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland Baltimore County (UMBC). He is a Life Fellow of IEEE and a Fellow of SPIE. He is an Associate Editor of Remote Sensing and IEEE Transaction on Geoscience and Remote Sensing. Dr. Chang has authored four books, edited two books, and co-edited one book.

• EDITOR BIOGRAPHY viiLIST OF CONTRIBUTORS viiiPREFACE xPART I GENERAL THEORY 11 Introduction: Two Fundamental Principles Behind Hyperspectral Imaging 3Chein-I Chang2 Overview of Hyperspectral Imaging Remote Sensing from Satellites 41Shen-En Qian3 Efficient Hardware Implementation for Hyperspectral Anomaly and Target Detection 67Jie Lei, Weiying Xie, Jiaojiao Li, Keyan Wang, Kai Liu, and Yunsong LiPART II BAND SELECTION FOR HYPERSPECTRAL IMAGING 1074 Constrained Band Selection for Hyperspectral Imaging 109Chein-I Chang5 Band Subset Selection for Hyperspectral Imaging 147Chein-I Chang6 Progressive Band Selection Processing for Hyperspectral Image Classification 179Chunyan Yu, Meiping Song, and Chein-I ChangPART III COMPRESSIVE SENSING FOR HYPERSPECTRAL IMAGING 2057 Restricted Entropy and Spectrum Properties for Hyperspectral Imaging 207Chein-I Chang and Bernard Lampe8 Endmember Finding in Compressively Sensed Band Domain 228Chein-I Chang and Adam Bekit9 Hyperspectral Image Classification in Compressively Sensed Band Domain 252Charles J. Della-Porta and Chein-I ChangPART IV FUSION FOR HYPERSPECTRAL IMAGING 27910 Hyperspectral and LiDAR Data Fusion 281Qian Du, Wei Li, and Chiru Ge11 Hyperspectral Data Fusion Using Multidimensional Information 293Lifu Zhang, Xia Zhang, Mingyuan Peng, Xuejian Sun, and Xiaoyang Zhao12 Fusion of Band Selection Methods for Hyperspectral Imaging 341Yulei Wang, Lin Wang, and Chein-I ChangPART V HYPERSPECTRAL DATA UNMIXING 36313 Model-Inspired Deep Neural Networks for Hyperspectral Unmixing 365Yuntao Qian, Fengchao Xiong, Minchao Ye, and Jun Zhou14 Analytical Fully Constrained Least Squares Linear Spectral Mixture Analysis 404Chein-I Chang and Hsiao-Chi Li15 Swarm Intelligence Optimization-Based Spectral Unmixing 422Lianru Gao, Xu Sun, Zhu Han, Lina Zhuang, Wenfei Luo, and Bing Zhang16 Spectral-Spatial Robust Nonnegative Matrix Factorization for Hyperspectral Unmixing 453Risheng Huang, Xiaorun Li, and Liaoying ZhaoPART VI HYPERSPECTRAL IMAGE CLASSIFICATION 48317 Sparse Representation-Based Hyperspectral Image Classification 485Haoyang Yu, Jun Li, Wei Li, and Bing Zhang18 Collaborative Classification Based on Hyperspectral Images 506Junping Zhang, Xiaochen Lu, and Tong Li19 Class Feature-Weighted Hyperspectral Image Classification 543Shengwei Zhong, Jiaojiao Li, Xiaodi Shang, Shuhan Chen, and Chein-I Chang20 Target Detection Approaches to Hyperspectral Image Classification 565Chein-I Chang, Bai Xue, and Chunyan YuINDEX 586