Hyperspectral Imaging

1. INTRODUCTION1.1. Hyperspectral Images. From Remote sensing to bench top instruments. A general overview1.2. Hyperspectral cameras. Types of hyperspectral cameras, radiations and sensors 2. ALGORITHMS AND METHODS2.1. Pre-processing of hyperspectral images. Spatial and spectral issues2.2. Hyperspectral data compression2.3. Pansharpening2.4. Unsupervised pattern recognition methods2.5. Multivariate Curve Resolution2.6. Non Linear Spectral un-mixing2.7. Variability of the endmembers in spectral unmixing2.8. Regression models2.9. Classical Least Squares for Detection and Classification2.10. Supervised Classification Methods in Hyperspectral Imaging - Recent Advances2.11. Fusion of Hyperspectral Imaging and LiDAR for Forest Monitoring2.12. Hyperspectral time series analysis: Hyperspectral image data streams interpreted by modeling known and unknown variations2.13. Statistical Biophysical Parameter Retrieval and Emulation with Gaussian Processes 3. APPLICATION FIELDS3.1. Hyperspectral cameras adapted to the applications. How and when3.2. Applications in Remote Sensing - Natural Landscapes3.3. Applications in Remote Sensing - Anthropogenic activities3.4. Vegetation and crops3.5. Food and feed production3.6. Hyperspectral Imaging for Food related Microbiology Applications3.7. Hyperspectral Imaging in Medical Applications3.8. Hyperspectral Imaging as a part of Pharmaceutical Product Design3.9. Hyperspectral imaging for artworks investigation3.10. Growing applications of hyperspectral and multispectral imaging