To establish the theoretical foundation of fundamental digital image processing concepts.
To establish mathematical principles for digital image processing, including image acquisition, preprocessing, segmentation, Fourier transform operations, and compression.
To acquire expertise and practical skills in programming using MATLAB for digital image processing, including picture acquisition, preprocessing, segmentation, Fourier transform, and compression.
Prerequisite(s)
None
Corequisite(s)
None
Special Requisite(s)
Fundamental signal processing, matrix operations, and a basic knowledge of MATLAB / Python Open CV are expected.
Instructor(s)
Assist. Prof. Dr. Necip Gökhan KASAPOĞLU
Course Assistant(s)
None
Schedule
Lecture: Wednesday 11:00 – 12:50 (Sec. A, B), Lab: Wednesday 13:00 – 14:50 (Sec. A), 15:00 – 16:50 (Sec. B)
Two-Dimensional Signal and Image Processing, Jae S. Lim, Printice Hall.
Digital Image Processing, Rafael C. Gonzales and Richard E. Woods, Pearson.
Other Sources
Computer Vision: Algorithms and Applications, Richards Szeliski, Springer, 2010 (click here to download).
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction, image formation
Oral presentations and MATLAB / Python Open CV applications
2. Week
Point processing
Oral presentations and MATLAB / Python Open CV applications
3. Week
Spatial processing 1
Oral presentations and MATLAB / Python Open CV applications
4. Week
Spatial processing 2
Oral presentations and MATLAB / Python Open CV applications
5. Week
Frequency domain techniques
Oral presentations and MATLAB / Python Open CV applications
6. Week
Image restoration 1
Oral presentations and MATLAB / Python Open CV applications
7. Week
Image restoration 2
Oral presentations and MATLAB / Python Open CV applications
8. Week
Midterm
Classical written exam
9. Week
Image segmentation 1
Oral presentations and MATLAB / Python Open CV applications
10. Week
Image segmentation 2
Oral presentations and MATLAB / Python Open CV applications
11. Week
Mathematical morphology
Oral presentations and MATLAB / Python Open CV applications
12. Week
Color processing
Oral presentations and MATLAB / Python Open CV applications
13. Week
Image coding and compression 1
Oral presentations and MATLAB / Python Open CV applications
14. Week
Image coding and compression 2
Oral presentations and MATLAB / Python Open CV applications
15. Week
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
30
Homework / Term Projects / Presentations
1
5
Project(s)
1
20
Attendance
1
5
Final Exam
1
40
Program Outcomes
PO-1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
PO-3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
PO-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11
Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.
Learning Outcomes
LO-1
Comprehend the fundamental principles of digital image processing.
LO-2
Ability to analyze images in the frequency domain.
LO-3
Use and analyze image enhancement and restoration techniques.
LO-4
Color image processing can be performed.
LO-5
Demonstrate ability in applying picture segmentation and representation techniques and interpreting the outcomes.
