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
Advanced Topics in Digital Image Processing MDES672 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
Consent of the Instructor
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
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;
  • 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 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
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
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
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
Percentage of Final Work 20
Total 100

Course Category

Core Courses X
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 Ability to carry out advanced research activities, both individual and as a member of a team
2 Ability to evaluate research topics and comment with scientific reasoning
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level
7 Contribute scientific and technological advancements on engineering domain of his/her interest area
8 Contribute industrial and scientific advancements to improve the society through research activities

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