"Processing and Analysis of Hyperspectral Data" ed. by Jie Chen, Yingying Song, Hengchao Li

This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods.

Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis.


Contents
1.Hyperspectral Endmember Extraction Techniques
2.Hyperspectral Image Classification
3.Hyperspectral Image Super-Resolution Using Optimization and DCNN-Based Methods
4.Fast Chaotic Encryption for Hyperspectral Images
5.NIR Hyperspectral Imaging for Mapping of Moisture Content Distribution in Tea Buds during Dehydration
6.Use of Hyperspectral Remote Sensing to Estimate Water Quality