i

Title of Course

Satellite Image Analysis Theory (NR 803)

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Credit Sructure

        L            T          P           C

        3            0           0            6

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Prerequisite, if any (for the students)

A course in digital image processing                                                        (equivalent to EE610, NR607)

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Course Content

Image Modeling, Multisensor Data Fusion, Object Oriented Image Analysis, Content Based Image Retrieval, Soft Computing,        Active Contour Models, Image Compression, Feature Selection Algorithms, Support Vector Machines, Multiresolution Image Analysis, Mathematical Morphology

v

Text / References

1. L. Shapiro and G. Stockman, Computer Vision, Prentice-Hall,    Englewood Cliffs, 2001

2. B. Tso and P.M. Mather, Techniques for Classification of Remotely Sensed Images, John Wiley, New York, 2001.

3. S.Z. Li, Markov Random Field Modeling in Computer Vision,

Springer, Berlin, 1996.

4. P. Soille, Morphological Image Analysis, Springer, Berlin, 1999.

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Instructor(s) name

  Dr. B. Krishnamohan

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Name of Other departments to whom the course is relevant

 Civil Engineering, Earth Sciences, CESE, Electrical Engineering

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Justification

The curriculum topics are essential to understand the basic premise of majority of the theories and techniques currently evolving through worldwide research in the area of digital image processing as applied to satellite remotely sensed images.