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Chang C.-I Real-Time Recursive Hyperspectral Sample and Band Processing. Algorithm Architecture and Implementation

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Chang C.-I Real-Time Recursive Hyperspectral Sample and Band Processing. Algorithm Architecture and Implementation
Springer, 2017. — 694 p.
This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing (/file/2040104/), published by Springer in 2016.
Introduction
Part I Fundamentals
Simplex Volume Calculation
Discrete-Time Kalman Filtering for Hyperspectral Processing
Target-Specified Virtual Dimensionality for Hyperspectral Imagery
Part II Sample Spectral Statistics-Based Recursive Hyperspectral Sample Processing
Real-Time Recursive Hyperspectral Sample Processing for Active Target Detection: Constrained Energy Minimization
Real-Time Recursive Hyperspectral Sample Processing for Passive Target Detection: Anomaly Detection
Part III Signature Spectral Statistics-Based Recursive Hyperspectral Sample Processing
Recursive Hyperspectral Sample Processing of Automatic Target Generation Process
Recursive Hyperspectral Sample Processing of Orthogonal Subspace Projection
Recursive Hyperspectral Sample Processing of Linear Spectral Mixture Analysis
Recursive Hyperspectral Sample Processing of Maximum Likelihood Estimation
Recursive Hyperspectral Sample Processing of Orthogonal Projection-Based Simplex Growing Algorithm
Recursive Hyperspectral Sample Processing of Geometric Simplex Growing Algorithm
Part IV Sample Spectral Statistics-Based Recursive Hyperspectral Band Processing
Recursive Hyperspectral Band Processing for Active Target Detection: Constrained Energy Minimization
Recursive Hyperspectral Band Processing for Passive Target Detection: Anomaly Detection
Part V Signature Spectral Statistics-Based Recursive Hyperspectral Band Processing (RHBP)
Recursive Hyperspectral Band Processing of Automatic Target Generation Process
Recursive Hyperspectral Band Processing of Orthogonal Subspace Projection
Recursive Hyperspectral Band Processing of Linear Spectral Mixture Analysis
Recursive Hyperspectral Band Processing of Growing Simplex Volume Analysis
Recursive Hyperspectral Band Processing of Iterative Pixel Purity Index
Recursive Band Processing of Fast Iterative Pixel Purity Index
Recursive Band Processing of Fast Iterative Pixel Purity Index
Conclusions
A: Matrix Identities
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