Techniques and Applications of Hyperspectral Image Analysis
Published on 27. September 2007
390 pages
978-0-470-01087-7 (ISBN)
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.
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Hans Grahn | Paul Geladi
Techniques and Applications of Hyperspectral Image Analysis
Software
11/2007
Wiley
€103.26
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Hans Grahn | Paul Geladi
Techniques and Applications of Hyperspectral Image Analysis
Book
09/2007
Wiley
€162.00
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Persons
Paul Geladi received a Ph.D. in chemistry at the Universityof Antwerp in 1979. In 1990, he became associate professor atUmeå University, with interests in multivariate calibration,multivariate image analysis and multiway analysis. He was awardedthe EAS award for Chemometrics in 2002. Currently he is head ofresearch for NIRCE centered in Umeå and Vasa. Paul Geladi hascoauthored about 90 scientific papers and some 20 book chapters andhas given many invited lectures throughout Europe and NorthAmerica. He was European editor of Journal of Chemometrics from1989 - 1995, and has been review editor of the journal since 1999.He served as a member of the Editorial Board of Chemometrics andIntelligent Laboratory Systems from 1986 to 1991.
Hans F Grahn received his Ph.D. in Physical OrganicChemistry in 1986. Following several years of work abroad he beganMRI studies in the laboratory of Dr Zeverenyi at SUNY HealthCenter, NY. At this time (1988) Hans also began to collaborate withPaul Geladi and the MIA (Multivariate Image Analysis) software forMRI multivariate images was written. In 1990 Hans received fundingfrom the Swedish Natural Science Foundation for 2D NMR work atUmeå University. In 1991 he began a 3 year project atAstraZeneca. During this period he continued to collaborate withthe pharmaceutical industry and the Karolinska Institute, where hereceived a position as a preclinical researcher and associateProfessor at a new MRI -centre. Hans has more than 35 coauthoredscientific papers and book chapters. He is now active as BusinessDeveloper in the Medical Imaging business and is also active in hisown company.
Content
Preface.
List of Contributors.
List of Abbreviations.
1 Multivariate Images, Hyperspectral Imaging: Background andEquipment (Paul L. M. Geladi, Hans F. Grahn and James E.Burger).
2 Principles of Multivariate Image Analysis (MIA) in RemoteSensing, Technology and Industry (Kim H. Esbensen andThorbjørn T. Lied).
3 Clustering and Classification in Multispectral Imaging forQuality Inspection of Postharvest Products (Jacco C. Noordam andWillie H. A. M. van den Broek).
4 Self-modeling Image Analysis with SIMPLISMA (Willem Windig,Sharon Markel and Patrick M. Thompson).
5 Multivariate Analysis of Spectral Images Composed of CountData (Michael R. Keenan).
6 Hyperspectral Image Data Conditioning and Regression Analysis(James E. Burger and Paul L. M. Geladi).
7 Principles of Image Cross-validation (ICV): RepresentativeSegmentation of Image Data Structures (Kim H. Esbensen andThorbjørn T. Lied).
8 Detection, Classification, and Quantification in HyperspectralImages Using Classical Least Squares Models (Neal B.Gallagher).
9 Calibration Standards and Image Calibration (Paul L. M.Geladi).
10 Multivariate Movies and their Applications in Pharmaceuticaland Polymer Dissolution Studies (Jaap van der Weerd and SergeiG. Kazarian).
11 Multivariate Image Analysis of Magnetic Resonance Images:Component Resolution with the Direct Exponential Curve ResolutionAlgorithm (DECRA) (Brian Antalek, Willem Windig and Joseph P.Hornak).
12 Hyperspectral Imaging Techniques: an Attractive Solution forthe Analysis of Biological and Agricultural Materials (VincentBaeten, Juan Antonio Fernández Pierna and PierreDardenne).
13 Application of Multivariate Image Analysis in NuclearMedicine: Principal Component Analysis (PCA) on Dynamic Human BrainStudies with Positron Emission Tomography (PET) for Discriminationof Areas of Disease at High Noise Levels (Pasha Razifar and MatsBergström).
14 Near Infrared Chemical Imaging: Beyond the Pictures (E.Neil Lewis, Janie Dubois, Linda H. Kidder and Kenneth S.Haber).
Index.
