Basic theory and main processing techniques of hyperspectral remote sensing -- Classification technique for HSI -- Endmember extraction technique of HSI -- Spectral unmixing technique of HSI -- Sub-pixel mapping technique of HSI -- Super-resolution technique of HSI -- Anomaly detection technique of HSI -- Dimensionality reduction and compression technique of HSI -- Introduction to hyperspectral remote sensing applications.

Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping, and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.