'Hyperspectral Imaging Analysis' is an elective course offered for the B. Tech. (Bachelor of Technology) in Electronics and Communication Engineering at School of Engineering, Amrita Vishwa Vidyapeetham.
Unit 1
Introduction to Remote Sensing: Multi-Spectral Imagery (MSI) - Hyperspectral Imagery (HSI) - Scientific Principles: Physics of imaging spectroscopy - electromagnetic propagation - sensor physics - atmospheric Corrections - Hyperspectral Concepts and System Tradeoffs: Signal-to-Noise ratio (SNR) - spectral resolution– sampling – range.
Unit 2
Dispersion Techniques – data collection systems – current HIS systems: Ground – airborne – spaceborne – calibration techniques – HSI Data Processing Software – HSI Data Processing Techniques: Image Space – spectral space - feature space, spectral angle mapping - N-dimensional scatterplots - projection pursuit – spectral mixture analysis – Principal Component Analysis (PCA).
Unit 3
Spectral mapping – Pixel Purity Index (PPI) – Minimum Noise Fraction (MNF) – Mixture Tuned Matched Filtering (MTMF) – Classification Techniques: Supervised – Unsupervised – Hybrid - Detection, Classif ication, and Quantif ication in Hyperspectral Images Using Classical Least Squares Models.
TEXTBOOKS
- Chein-I-Chang, “Hyperspectral Techniques for Spectral Detection and Classification Graphics and General-Purpose Computation,” Kluwer Academic Publishers, 2003.
TEXTBOOKS
- James B. Campbell and Randolph H. Wynne, “Introduction to Remote Sensing“, Guilford Press, Fifth Edition, 2011.
- Hans F. Grahn and Paul Geladi, “Techniques and Applications of Hyperspectral Image Analysis, “John Wiley & Sons Ltd, 2007.
