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.

Systematically provides a complete framework of the novel processing techniques of hyperspectral imaging Introduces from the basic theory to the state of the art techniques and their applications to meet the needs of readers at different levels Aims at the two hot topics in HSI processing, i.e. high accuracy and real time Includes supplementary material: sn.pub/extras

Contenu
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.