Hyperspectral Image Processing
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Beschreibung
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.
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
Autor*in
Liguo Wang
Themen in »Hyperspectral Image Processing«
Anomaly Detection Endmember Extraction Hyperspectral Imaging (HSI) Image Processing Remote Sensing SVM-based Classification Spectral Unmixing Sub-pixel Mapping Super-resolution remote sensing/photogrammetry