Kernel Methods:  Introduction to metric space, vector space, normed space, inner product space; RKHS; Learning theory;  SVM for classification & regression; implementation techniques of SVM;   kernel ridge regression;  kernel density estimation;  kernel PCA; kernel online learning.Random forest, Genetic algorithms, ant colony optimization

Spectral Clustering; model based clustering, Expectation Maximization; Independent Component Analysis; Hidden Markhov models;  Factor Analysis; introduction to Graphical models & Sampling Methods.

Programming in the context of processing of raster, vector and tabular geospatial data.Basic principles of programming, including languages and syntax, paradigms, variables, control flow and functions. IDL, python, and R. Image spatial datastructures - and spatial databases – Structured query language- ADT, spatial ADTs and their operations,Spatial data structures and spatial indexing.

Linear Algebra:  n- dimensional Euclidean spaces, linear transformation, Matrices, Eigen values and Eigen vectors, Generalised  inverses, SVD.

Numerical Methods: Numerical Solution of nonlinear equations, Direct and iterative methods to solve system of linear equations, Numerical integration – Trapezoidal and Simpson’s rule, Interpolation, Splines and curve fitting, Numerical solution of ODE –Euler’s method and 4th order Runge- Kutta Method.

Introduction: Basics of geometrics, Projection and coordinate system, Camera calibration - representation of digital images B/W, RGB, HIS, CCD cameras, time delay integration, spectral sensitivity of CCD sensor, geometry problem of CCD image - , image measurement, coordinate system, image movement, image transformation, geometric and radiometric transformation - Vertical aerial photographs: Parallax, Stereo model - Tilted photos: Rectification, Mathematical photogrammetric principles, Analog vs Analytical vs Digital models - Orientation: Interior, Relative, Absolute - Collinearity and Copla

Electromagnetic radiation and its interaction with matter, Spectral signatures, image formation remote sensors and platforms, resolutions, radiometric and geometric distortions, thermal remote sensing, spectral indices, classification techniques, image transformations, intensity transformations, spatial filtering, image formats, noise reduction, image segmentation.Introduction to Geographic Information System (GIS) - Hardware, Software, Data types and models-Spatial data quality, Thematic maps, Symbolization, Scale and generalization - Co-ordinate systems, Map projections and visualization

Electromagnetic radiation and its interaction with matter, Spectral signatures, image formation remote sensors and platforms, resolutions, radiometric and geometric distortions, thermal remote sensing, spectral indices, classification techniques, image transformations, intensity transformations, spatial filtering, image formats, noise reduction, image segmentation.