(Ebook PDF) Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging 1st Edition by Cyril Ruckebusch 0444636447 9780444636447 full chapters

Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging 1st Edition by Cyril Ruckebusch 0444636447 9780444636447 – Ebook PDF Instant Download/DeliveryISBN: 

Full download Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging 1st Edition after payment.

Product details:

ISBN-10 :  0444636447 

ISBN-13 : 9780444636447

Author: Cyril Ruckebusch 

Resolving Spectral Mixtures: With Applications from Ultrafast Time-Resolved Spectroscopy to Superresolution Imaging offers a comprehensive look into the most important models and frameworks essential to resolving the spectral unmixing problem—from multivariate curve resolution and multi-way analysis to Bayesian positive source separation and nonlinear unmixing. Unravelling total spectral data into the contributions from individual unknown components with limited prior information is a complex problem that has attracted continuous interest for almost four decades.

Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging 1st Table of contents:

Chapter 1: Introduction
Abstract
1 Introduction
2 The Spectral Mixture Problem
3 Book Content and Organization
Chapter 2: Multivariate Curve Resolution-Alternating Least Squares for Spectroscopic Data
Abstract
1 MCR: The Concept and the Link with Spectroscopic Data
2 MCR-ALS: Algorithm and Data Set Configuration
3 MCR-ALS Applied to Process Analysis
4 MCR-ALS Applied to HSI Analysis
5 MCR-ALS and Quantitative Analysis
6 MCR-ALS and Other Bilinear Decomposition Methods
Chapter 3: Spectral Unmixing Using the Concept of Pure Variables
Abstract
1 Introduction
2 Case Studies
3 Spectral Unmixing with Pure Variables
4 Chasing the Pure Variables
5 Investigation of Purity Characteristics
6 Other Ways to Find the Pure Variables
7 Pure Variables and MCR-ALS
8 Discussion and Conclusions
Chapter 4: Ambiguities in Multivariate Curve Resolution
Abstract
1 Multivariate Curve Resolution and Ambiguities
2 Evaluation of MCR Ambiguities
3 Estimation of the Extension of Rotation Ambiguities and of Their MCR Feasible Solutions
4 MCR Constraints and Their Implementation
5 Implementation of the MCR-BANDS Method
6 Example of Calculation of MCR Feasible Solutions Using the MCR-BANDS Method
7 Comparison of Solutions Obtained by Different MCR Methods
8 Comparison of the Ranges of MCR Feasible Solutions Obtained by Different Methods
9 Conclusions
Chapter 5: On the Analysis and Computation of the Area of Feasible Solutions for Two-, Three-, and Four-Component Systems
Abstract
1 Introduction
2 MCR Methods
3 The Area of Feasible Solutions
4 The AFS for Two-Component Systems
5 Feasibility of Points in the AFS
6 AFS Computations for Three-Component Systems
7 AFS Computations for Four-Component Systems
8 Reduction of the Rotational Ambiguity by Soft Constraints Represented in the AFS
9 Geometric Shapes of the AFS and AFS Dynamics
10 The FACPACK Toolbox for AFS Computations
11 Outlook and Open Problems
Chapter 6: Linear and Nonlinear Unmixing in Hyperspectral Imaging
Abstract
1 Spectral Mixture Analysis
2 Linear Unmixing
3 Nonlinear Unmixing
4 Experiments: Unmixing EELS Data
5 Conclusion
Acknowledgments
Chapter 7: Independent Components Analysis: Theory and Applications
Abstract
1 Introduction
2 Theory
3 Some Applications of ICA
4 Conclusion
Chapter 8: Bayesian Positive Source Separation for Spectral Mixture Analysis
Abstract
1 Introduction
2 Geometrical Interpretation of the NMF Model
3 The Bayesian Positive Source Separation Algorithm
4 Applications
5 Conclusion
Chapter 9: Multivariate Curve Resolution of Wavelet Compressed Data
Abstract
1 Introduction
2 Theory
3 Experimental Details
4 Discussion of Results
5 Conclusion
Acknowledgments
Chapter 10: Chemometric Resolution of Complex Higher Order Chromatographic Data with Spectral Detection
Abstract
1 Introduction
2 Instrument Design and Utilization to Produce High-Order Chemical Separations Data
3 Chemometric Resolution Methods
4 Applications and Conclusions
Chapter 11: Multivariate Curve Resolution of (Ultra)Fast Photoinduced Process Spectroscopy Data
Abstract
1 Introduction
2 Photoinduced Processes
3 Time-Resolved Spectroscopy
4 MCR of TRS Data
5 Applications
6 Concluding Remarks
Chapter 12: Experimental and Data Analytical Approaches to Automating Multivariate Curve Resolution in the Analysis of Hyperspectral Images
Abstract
1 Introduction
2 Theory of MCR Analyses
3 Approaches to Improve the Probability of Successful MCR Solutions
4 Comparison of Standard and Automated Preprocessing Approaches to MCR Analyses of Realistically Simulated and Real Hyperspectral Confocal Fluorescence Images
5 Conclusions
Acknowledgments
Chapter 13: Multiresolution Analysis and Chemometrics for Pattern Enhancement and Resolution in Spectral Signals and Images
Abstract
1 Introduction
2 Methods
3 Applications
4 Remarks
Acknowledgments
Chapter 14: A Smoothness Constraint in Multivariate Curve Resolution-Alternating Least Squares of Spectroscopy Data
Abstract
1 Introduction
2 Smoothing Signals and Images
3 Smoothness Constraints in MCR-ALS
4 Case Studies
5 Concluding Remarks
Acknowledgments
Chapter 15: Super-Resolution in Vibrational Spectroscopy: From Multiple Low-Resolution Images to High-Resolution Images
Abstract
1 Introduction
2 The Super-Resolution Concept
3 Criteria to Measure the Spatial Resolution in Imaging Spectroscopy
4 Case Study #1: Super-Resolution Concept in MIR Spectroscopy [16]5 Optimization and Study of the Super-Resolution Concept in Near-Infrared Spectroscopy [19]6 Optimization and Study of the Super-Resolution Concept for Raman Confocal Imaging [24]7 Conclusion
Chapter 16: Multivariate Curve Resolution for Magnetic Resonance Image Analysis: Applications in Prostate Cancer Biomarkers Development
Abstract
1 Introduction
2 State-of-the-Art Methods
3 New Biomarkers Development
4 Conclusions
Acknowledgments
Chapter 17: Endmember Library Approaches to Resolve Spectral Mixing Problems in Remotely Sensed Data: Potential, Challenges, and Applications
Abstract
1 Introduction
2 Endmember Library-Based SMA Approaches
3 Challenges of Endmember Library-Based SMA Approaches
4 Applications of Endmember Library Approaches to Resolve Spectral Mixing Problems in Remotely Sensed Data
5 Conclusions
Acknowledgments
Chapter 18: Spectral–Spatial Unmixing Approaches in Hyperspectral VNIR/SWIR Imaging
Abstract
1 Introduction
2 Background on Linear Spectral Unmixing
3 Use of Spatial Information in Unmixing Process
4 Conclusions
Chapter 19: Sparse-Based Modeling of Hyperspectral Data
Abstract
1 Introduction
2 Theory: Sparse Methods
3 Sparse-Based Image Exploration: Applications
4 Conclusions

People also search for Resolving Spectral Mixtures With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging 1st:

spectral mixing
    
resolution of spectrometer
    
spectral mixture analysis
    
spectrometer resolving power
    
spectral resolution formula

Tags:

Spectral Mixtures,Applications,Ultrafast,Time Resolved,Spectroscopy,Super Resolution,Cyril Ruckebusch