FC31327 Digital Image Processing
Course Outline
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Course |
: FC 31327 – Digital Image Processing |
|
Core/Specialization |
: Core |
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Programme |
: Bachelor of Science Honors in Surveying Sciences |
|
Department |
: Cartography, Photogrammetry, Remote Sensing and GIS |
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Faculty |
: Faculty of Geomatics |
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Contact Hours |
: 150 |
|
Year |
: III |
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Semester |
: I |
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Lecturer |
: Ms. J. A. S. Jayakody |
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Room No. |
: FF-12 |
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Telephone No. |
: 045-3453019 |
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|
: swarna@geo.sab.ac.lk |
Synopsis
This course introduces the satellite image enhancement, classification, accuracy assessment and applications.
Contents
- Introduction to image enhancement
- Enhancement techniques
- Stretching
- Colour composite images
- Image classification
- Image analysis
- Filters
- Remote sensing applications
Practical Tasks
- Enhancement using ERDAS software
- Stretching using ERDAS software
- Histogram Equalization using ERDAS software
- Colour composite images using ERDAS software
- Unsupervised classification using ERDAS software
- Supervised classification using ERDAS software
- Post classification using ERDAS software
- Principle Component analysis using ERDAS software
- Texture analysis ERDAS software
- PCA using ERDAS software
- Apply filtering techniques using ERDAS software
Learning Outcomes
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By the end of the course, students should be able to: |
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No. |
Course Learning Outcome |
Programme Outcome |
Assessment Methods |
|
1. |
Apply enhancement methods to the satellite images |
P01 |
Final Exam |
|
2. |
Identify the changes in applying different enhancement methods |
P01 |
Final Exam |
|
3. |
Use different classification methods and classify the images using ERDAS software |
P02 |
Assignment/ Final Exam |
|
4. |
Identify difficulties in the classification process |
P01 |
Final Exam |
|
5. |
Find the difficulties/advantages/ disadvantages in filtering. |
P01 |
Assignment/ Final Exam |
|
6. |
Detect the changes with the time period. |
P01 |
Final Exam |
Student Learning Time (SLT)
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Teaching and Learning Activities |
Student Learning Time (hours) |
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Directed Learning |
|
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Lectures and Student Centered Learning (SCL) |
28 |
|
Lab Practical |
40 |
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Independent Learning |
|
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Preparation - Student Centred Learning activities |
15 |
|
Lab Practical activities |
20 |
|
Self-Learning (Library & Internet) |
21 |
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Revision |
20 |
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Assessment |
|
|
Assignments |
02 |
|
Final Examination(written) |
02 |
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Final Examination(Practical) |
02 |
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TOTAL (SLT) |
150 |
Teaching Methodology
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Lectures, and individual and group assignments |
References
- Robert Shcowebgerdt, Remote sensing models & methods for image processing, III edition, 2004.
- John A.Richards, Springer – Verlag, Remote Sensing Digital Image Analysis 1999.
- W.G.Rees - Physical Principles of Remote Sensing, Cambridge University Press, 2nd edition, 2001.
- Paul M. Mather and Magaly Koch, Computer Processing of Remotely-Sensed Images, Fourth Edition.
- James B., Introduction to Remote Sensing, Camphell, Latest Edition
- Chandra, A.M., Remote Sensing and Geographical Information System – 2006
- Joseph, George, Fundamentals of Remote Sensing – 2005
- Rees, W.G., Physical Principles of Remote Sensing – 2005
- Richards, John A., Remote Sensing Digital Image Analysis : An Introduction – 2013
Grading
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Assignments |
20% |
|
Practical asignments & projects |
30% |
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Final Examination |
50% |
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Total |
100% |