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Real-Time Progressive Hyperspectral Image Processing Endmember Finding and Anomaly Detection /
The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new concepts of real time hyperspectral image processing, Progressive Hyperspectral Imaging (PHSI) and Recursive Hyperspectral Imaging (RHSI). Both of these can be us...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Overview and Introduction
- Part I: Preliminaries
- Linear Spectral Mixture Analysis
- Finding Endmembers in Hyperspectral Imagery
- Linear Spectral Unmixing with Three Criteria, Least Squares Error, Simplex Volume and Orthogonal Projection
- Hyperspectral Target Detection
- Part II: Sample-wise Sequential Processes for Finding Endmembers
- Abundance-Unconstrained Sequential Endmember Finding Algorithms: Orthogonal Projection
- Fully Abundance-Constrained Sequential Endmember Finding Algorithms: Simplex Volume Analysis
- Partially Abundance Non-Negativity-Constrained Endmember Finding Algorithms: Convex Cone Volume Analysis
- Fully Abundance-Constrained Sequential Linear Spectral Mixture Analysis for Finding Endmembers
- Part III: Sample-Wise Progressive Processes for Finding Endmembers
- Abundance-Unconstrained Progressive Endmember Finding Algorithms: Orthogonal Projection
- Fully Abundance-Unconstrained Progressive Endmember Finding Algorithms: Simplex Volume Analysis
- Partially Abundance Non-Negativity-Constrained Progressive Endmember Finding Algorithms: Convex Cone Volume Analysis
- Sully Abundance-Constrained Progressive Linear Spectral Mixture Analysis for Finding Endmembers
- Part IV: Sample-Wise Progressive Unsupervised Target Detection
- Progressive Anomaly Detection
- Progressive Adaptive Anomaly Detection
- Progressive Window-Based Anomaly Detection
- Progressive Subpixel Target Detectio n and Classification.