ECTS - Advanced Topics in Digital Image Processing
Advanced Topics in Digital Image Processing (MDES672) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Advanced Topics in Digital Image Processing | MDES672 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Ph.D. |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture. |
Course Lecturer(s) |
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Course Objectives | Upon successful completion of the course, students will learn and have an understanding of the mathematical tools for modeling and analysis of image acquisition and processing systems. Students will also master basic techniques of image processing applications. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Review of image processing fundamentals, frequency and space domain image processing methods; wavelets, multiresolution processing, and orthogonal transforms; image and video compression standards; image segmentation and representation; nonlinear image processing methods. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Review of image processing fundamentals | Related pages of lecture notes and other sources |
2 | Review of basic frequency and space domain image processing techniques | Related pages of lecture notes and other sources |
3 | Review of basic frequency and space domain image processing techniques | Related pages of lecture notes and other sources |
4 | Subband decomposition, filter banks, and pyramids | Related pages of lecture notes and other sources |
5 | Subband decomposition, filter banks, and pyramids | Related pages of lecture notes and other sources |
6 | Wavelets and discrete orthogonal transforms | Related pages of lecture notes and other sources |
7 | Wavelets and discrete orthogonal transforms | Related pages of lecture notes and other sources |
8 | Nonlinear image processing techniques | Related pages of lecture notes and other sources |
9 | Nonlinear image processing techniques | Related pages of lecture notes and other sources |
10 | Image segmentation | Related pages of lecture notes and other sources |
11 | Image representation and Description | Related pages of lecture notes and other sources |
12 | Image representation and Description | Related pages of lecture notes and other sources |
13 | Object Recognition | Related pages of lecture notes and other sources |
14 | Object Recognition | Related pages of lecture notes and other sources |
15 | Overall review | - |
16 | Final exam | - |
Sources
Course Book | 1. Ders notları / Notes are available |
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Other Sources | 2. 1. Digital Image Processing, Rafael C. Gonzales and Richard E. Woods, Addison-Wesley Publishing Company, 1993. |
3. 2. Digital Video Processing, A. Murat Tekalp, Prentice-Hall, 1995. | |
4. 3. Two-Dimensional Signal and Image Processing, Jae S. Lim, Prentice-Hall, 1989. | |
5. 4. Fundamentals of Digital Image Processing, Anil K. Jain and Thomas Kailath, Prentice-Hall 1988. | |
6. 5. Digital Image Processing, Kenneth R. Castleman, Prentice-Hall, 1995. |
Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | 4 | 20 |
Homework Assignments | - | - |
Presentation | - | - |
Project | 2 | 40 |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 20 |
Final Exam/Final Jury | 1 | 20 |
Toplam | 9 | 100 |
Percentage of Semester Work | 80 |
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Percentage of Final Work | 20 |
Total | 100 |
Course Category
Core Courses | X |
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Major Area Courses | |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | ||
1 | Develops the ability to apply advanced knowledge of mathematics, science, and engineering to the analysis, design, and optimization of complex systems. | |||||
2 | Implements long-term research and development studies in the major fields of Electrical and Electronics Engineering. | |||||
3 | Use modern engineering tools, techniques and facilities in design and other engineering applications. | X | ||||
4 | Does research actively on innovation and entrepreneurship. | |||||
5 | Develops the ability to effectively communicate and present research outcomes. | |||||
6 | Keeps up with recent advancements in science and technology and effectively accesses relevant information. | |||||
7 | Will have professional and ethical responsibility. | |||||
8 | Develops ability to effectively communications in both Turkish and English. | |||||
9 | Develops ability on project management. | |||||
10 | Develops the ability to work successfully at project teams in interdisciplinary fields. | X |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
---|---|---|---|
Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 16 | 2 | 32 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | 4 | 5 | 20 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 8 | 16 |
Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
Total Workload | 126 |