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.
|Publisher:||Springer Berlin Heidelberg|
|Edition description:||1st ed. 2016|
|Product dimensions:||6.10(w) x 9.25(h) x 0.04(d)|
Table of ContentsBasic 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.