Techniques and Applications of Hyperspectral Image Analysis Contributor(s): Grahn, Hans (Editor), Geladi, Paul (Editor) |
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ISBN: 047001086X ISBN-13: 9780470010860 Publisher: Wiley OUR PRICE: $215.60 Product Type: Hardcover - Other Formats Published: November 2007 Annotation: "Techniques and Applications of Hyperspectral Image Analysis" gives an introduction to the field of image analysis using hyperspectral techniques, and includes definitions and instrument descriptions. Other imaging topics that are covered are segmentation, regression and classification. The book discusses how high quality images of large data files can be structured and archived. Imaging techniques also demand accurate calibration, and are covered in sections about multivariate calibration techniques. The book explains the most important instruments for hyperspectral imaging in more technical detail. A number of applications from medical and chemical imaging are presented and there is an emphasis on data analysis including modeling, data visualization, model testing and statistical interpretation. |
Additional Information |
BISAC Categories: - Technology & Engineering | Imaging Systems |
Dewey: 621 |
LCCN: 2007021097 |
Physical Information: 1.07" H x 6.31" W x 9.12" (1.60 lbs) 392 pages |
Descriptions, Reviews, Etc. |
Publisher Description: Techniques and Applications of Hyperspectral Image Analysis gives an introduction to the field of image analysis using hyperspectral techniques, and includes definitions and instrument descriptions. Other imaging topics that are covered are segmentation, regression and classification. The book discusses how high quality images of large data files can be structured and archived. Imaging techniques also demand accurate calibration, and are covered in sections about multivariate calibration techniques. The book explains the most important instruments for hyperspectral imaging in more technical detail. A number of applications from medical and chemical imaging are presented and there is an emphasis on data analysis including modeling, data visualization, model testing and statistical interpretation. |