Postgraduate Course: Theory of Image Processing (PGGE11062)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Postgraduate Courses (School of GeoSciences) |
Other subject area | None |
| Course website |
http://www.geos.ed.ac.uk/postgraduate/MSc/mscprogrammes/remotesip/ |
Taught in Gaelic? | No |
| Course description | A theory based course on Image Processing techniques concentrating on the mathematical and physical models underlying the processing operations. Digital image representation and sampling aspects are followed by various processing techniques including point by point operations, noise models, filtering and de-convolution techniques, edge and line detection, stereo imaging, target tracking and elementary pattern recognition. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
The course will concentrate on the underlying physics and mathematics of processing techniquies, we aim to cover in the common material:
1: linear image formation and its underlying assumptions,
2: digital representation of image, the discrete Fourier Transform, its properties and implementation, Shannon sampling theorem, interpolation to zeroth and first order,
3: first order image statistics, point-by-point processing and histogram manipulation,
4: fixed pattern noise and random noise including underlying physics of Gaussian additive noise and methods of it estimation,
5: linear filtering in real and Fourier space, non-linear filters including shrink and expand, average threshold and median,
6: image restoration by inverse and Weiner filter, outline of CLEAN and maximum entropy restoration,
7: tomographic system and reconstruction by Fourier inversion and filtered back projection, outline of fan-beam system.
8: edge and line detection by first and second order differential edge detection, Hough Transform and its applications,
9: stereo imaging in parallel and converging geometry, outline of automated depth extraction techniques,
10: tracking by correlation, basic of statistical pattern recognition, examples of simple classifiers.
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Assessment Information
This course is assessed by:
one assignment(20%) and a written examination (80%).
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Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Will Hossack
Tel: (0131 6)50 5261
Email: |
Course secretary | Ms Caroline Keir
Tel: (0131 6)50 2543
Email: |
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