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Course Detail

Course Name Hyperspectral Imaging Analysis
Course Code 15ECE328
Program B. Tech. in Electronics and Communication Engineering
Year Taught 2019


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.

Text Books

  1. Chein-I-Chang, “Hyperspectral Techniques for Spectral Detection and Classification Graphics and General-Purpose Computation,” Kluwer Academic Publishers, 2003.


  1. James B. Campbell and Randolph H. Wynne, “Introduction to Remote Sensing“, Guilford Press, Fifth Edition, 2011.
  2. Hans F. Grahn and Paul Geladi, “Techniques and Applications of Hyperspectral Image Analysis, “John Wiley & Sons Ltd, 2007.

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