Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging 1st Edition Cyril Ruckebusch (Eds.) – eBook PDF
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Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging – Ebook PDF
Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging – Ebook PDF Instant Delivery – ISBN(s): 9780444636386,9780444636447,0444636382,0444636447
Product details:
- ISBN-10 : 0444636382
- ISBN-13 : 978-0444636386
- Author:
Table of contents:
Chapter 1: Introduction
Chapter 2: Multivariate Curve Resolution-Alternating Least Squares for Spectroscopic Data
Chapter 3: Spectral Unmixing Using the Concept of Pure Variables
Chapter 4: Ambiguities in Multivariate Curve Resolution
Chapter 5: On the Analysis and Computation of the Area of Feasible Solutions for Two-, Three-, and Four-Component Systems
Chapter 6: Linear and Nonlinear Unmixing in Hyperspectral Imaging
Chapter 7: Independent Components Analysis: Theory and Applications
Chapter 8: Bayesian Positive Source Separation for Spectral Mixture Analysis
Chapter 9: Multivariate Curve Resolution of Wavelet Compressed Data
Chapter 10: Chemometric Resolution of Complex Higher Order Chromatographic Data with Spectral Detection
Chapter 11: Multivariate Curve Resolution of (Ultra)Fast Photoinduced Process Spectroscopy Data
Chapter 12: Experimental and Data Analytical Approaches to Automating Multivariate Curve Resolution in the Analysis of Hyperspectral Images
Chapter 13: Multiresolution Analysis and Chemometrics for Pattern Enhancement and Resolution in Spectral Signals and Images
Chapter 14: A Smoothness Constraint in Multivariate Curve Resolution-Alternating Least Squares of Spectroscopy Data
Chapter 15: Super-Resolution in Vibrational Spectroscopy: From Multiple Low-Resolution Images to High-Resolution Images
Chapter 16: Multivariate Curve Resolution for Magnetic Resonance Image Analysis: Applications in Prostate Cancer Biomarkers Development
Chapter 17: Endmember Library Approaches to Resolve Spectral Mixing Problems in Remotely Sensed Data: Potential, Challenges, and Applications
Chapter 18: Spectral–Spatial Unmixing Approaches in Hyperspectral VNIR/SWIR Imaging
Chapter 19: Sparse-Based Modeling of Hyperspectral Data
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