Resolving Spectral Mixtures : With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging (Hardcover)

1. Introduction 2. Multivariate Curve Resolution-Alternating Least Squares for Spectroscopic Data 3. Spectral Unmixing Using the Concept of Pure Variables 4. Ambiguities in Multivariate Curve Resolution 5. On the Analysis and Computation of the Area of Feasible Solutions for Two-, Three-, and Four-Component Systems 6. Linear and Nonlinear Unmixing in Hyperspectral Imaging 7. Independent Components Analysis: Theory and Applications 8. Bayesian Positive Source Separation for Spectral Mixture Analysis 9. Multivariate Curve Resolution of Wavelet Compressed Data 10. Chemometric Resolution of Complex Higher Order Chromatographic Data with Spectral Detection 11. Multivariate Curve Resolution of (Ultra)Fast Photoinduced Process Spectroscopy Data 12. Experimental and Data Analytical Approaches to Automating Multivariate Curve Resolution in the Analysis of Hyperspectral Images 13. Multiresolution Analysis and Chemometrics for Pattern Enhancement and Resolution in Spectral Signals and Images 14. A Smoothness Constraint in Multivariate Curve Resolution-Alternating Least Squares of Spectroscopy Data 15. Super-Resolution in Vibrational Spectroscopy: From Multiple Low-Resolution Images to High-Resolution Images 16. Multivariate Curve Resolution for Magnetic Resonance Image Analysis: Applications in Prostate Cancer Biomarkers Development 17. Endmember Library Approaches to Resolve Spectral Mixing Problems in Remotely Sensed Data: Potential, Challenges, and Applications 18. Spectral-Spatial Unmixing Approaches in Hyperspectral VNIR/SWIR Imaging 19. Sparse-Based Modeling of Hyperspectral Data