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Hyperspectral Image Processing [electronic resource] / by Liguo Wang, Chunhui Zhao.

By: Wang, Liguo [author.].
Contributor(s): Zhao, Chunhui [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XVII, 315 p. 121 illus., 15 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662474563.Subject(s): Signal processing | Computer vision | Geographic information systems | Signal, Speech and Image Processing | Computer Vision | Geographical Information SystemAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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.
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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.

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