Hyperspectral imaging /
Clasificación: | Libro Electrónico |
---|---|
Otros Autores: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Amsterdam, Netherlands :
Elsevier,
[2020]
|
Colección: | Data handling in science and technology ;
v. 32. |
Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- I
- Introduction
- 1.1
- Hyperspectral and multispectral imaging: setting the scene
- 1.2
- Configuration of hyperspectral and multispectral imaging systems
- II
- Algorithms and methods
- 2.1
- Preprocessing of hyperspectral and multispectral images
- 2.2
- Hyperspectral compression
- 2.3
- Pansharpening
- 2.4. Unsupervised exploration of hyperspectral and multispectral images
- 2.5
- Multivariate curve resolution for hyperspectral image analysis
- 2.6
- Nonlinear spectral unmixing
- 2.7
- Variability of the endmembers in spectral unmixing
- 2.8
- An overview of regression methods in hyperspectral and multispectral imaging
- 2.9
- Classical least squares for detection and classification
- 2.10
- Supervised classification methods in hyperspectral imaging--recent advances
- 2.11
- Fusion of hyperspectral imaging and LiDAR for forest monitoring
- 2.12
- Hyperspectral time series analysis: hyperspectral image data streams interpreted by modeling known and unknown variations
- 2.13
- Statistical biophysical parameter retrieval and emulation with Gaussian processes
- III
- Application fields
- 3.1
- Applications in remote sensing--natural landscapes
- 3.2
- Applications in remote sensing--anthropogenic activities
- 3.3
- Hyperspectral imaging in crop fields: precision agriculture
- 3.4
- Food and feed production
- 3.5
- Hyperspectral imaging for food-related microbiology applications
- 3.6
- Hyperspectral imaging in medical applications
- 3.7. Hyperspectral imaging as a part of pharmaceutical product design
- 3.8
- Hyperspectral imaging for artworks investigation
- 3.9
- Growing applications of hyperspectral and multispectral imaging