Postgraduate Course: Image Processing (PGEE11021)
Course Outline
| School | School of Engineering |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | Students study elements of image processing theory and application through the application of signal processing techniques. The syllabus of the course is:
1. Introduction: Basic concepts of vision and images.
2. Image transforms: SVD, Haar, Walsh, Fourier and derived methods.
3. Statistical description of images, including the Karhunen-Loeve Transform.
4. Image enhancement: Filters, Removing noise and interference, Histogram manipulation.
5. Image restoration: including inverse and Wiener filters.
6. Image segmentation and edge detection.
7. Image processing for multispectral images.
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| Course description |
Lectures and tutorials
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2017/18, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 22,
Seminar/Tutorial Hours 11,
Formative Assessment Hours 1,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
62 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% closed-book formal written examination |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S1 (December) | Image Processing | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- The students will understand and apply the fundamental techniques and algorithms behind multiple image processing applications. By the end of this module, the students should be able to:
- Understand how signal processing techniques generalise from univariate signals to images.
- Recall a range of techniques and algorithms for image processing.
- Demonstrate critical knowledge of commonly use image processing techniques, being able to discuss their advantages and disadvantages in specific applications.
- Apply analytically the key techniques for image transformation, enhancement, restoration and segregation to simple images.
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Reading List
Maria Petrou and Costas Petrou, Image Processing: The fundamentals, 2nd Edition, Wiley, 2010
"Digital Image Processing", 3rd Ed, by Gonzalez & Woods,
ISBN-10: 0132345633, ISBN-13: 9780132345637 |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | image signal processing,feature extraction,segmentation and classification,transforms |
Contacts
| Course organiser | Dr Javier Escudero Rodriguez
Tel: (0131 6)50 5599
Email: |
Course secretary | Miss Megan Inch
Tel: (0131 6)51 7079
Email: |
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