ACADEMICS
Course Details

ELE775 - Image Processing

2022-2023 Fall term information
The course is not open this term
ELE775 - Image Processing
Program Theoretýcal hours Practical hours Local credit ECTS credit
PhD 3 0 3 10
Obligation : Elective
Prerequisite courses : -
Concurrent courses : -
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer
Course objective : In order to equip the students with the capability to solve real-life problems in image processing, this course aims to teach the following topics to the students: basic concepts of image processing , image enhancement, restoration and compression, image segmentation and image representation for object recognition
Learning outcomes : Know the basic concepts and approaches in image processing, Apply the techniques and algorithms s/he learnt in the class in real-life applications, Have the adequate knowledge to follow and understand advanced up-to-date image processing techniques.
Course content : Basics of image processing: Spatial and Frequency Domains. Image enhancement. Image restoration. Multiresolution image processing. Image compression. Image segmentation. Image representation and description for object recognition.
References : Gonzalez R. C., Woods R. E., Digital Image Processing, 3rd ed., Prentice-Hall, 2008.
Course Outline Weekly
Weeks Topics
1 Basic concepts in image processing
2 Image enhancement in the spatial domain
3 Image transforms
4 Image enhancement in the frequency domain
5 Image restoration
6 Color spaces and color image processing
7 Multiresolution image processing: Wavelets
8 Midterm Exam
9 Image compression
10 Image coding
11 Morphologic operations
12 Image segmentation
13 Image representation and description
14 Introduction to object recognition
15 Preparation week for final exams
16 Final exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 0 0
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 8 40
Presentation 0 0
Project 0 0
Seminar 0 0
Quiz 0 0
Midterms 1 20
Final exam 1 40
Total 100
Percentage of semester activities contributing grade success 60
Percentage of final exam contributing grade success 40
Total 100
Workload and ECTS Calculation
Course activities Number Duration (hours) Total workload
Course Duration 14 3 42
Laboratory 0 0 0
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 14 10 140
Presentation / Seminar Preparation 0 0 0
Project 0 0 0
Homework assignment 8 9 72
Quiz 0 0 0
Midterms (Study duration) 1 20 20
Final Exam (Study duration) 1 25 25
Total workload 38 67 299
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Has highest level of knowledge in certain areas of Electrical and Electronics Engineering.
2. Has knowledge, skills and and competence to develop novel approaches in science and technology.
3. Follows the scientific literature, and the developments in his/her field, critically analyze, synthesize, interpret and apply them effectively in his/her research.
4. Can independently carry out all stages of a novel research project.
5. Designs, plans and manages novel research projects; can lead multidisiplinary projects.
6. Contributes to the science and technology literature.
7. Can present his/her ideas and works in written and oral forms effectively; in Turkish or English.
8. Is aware of his/her social responsibilities, evaluates scientific and technological developments with impartiality and ethical responsibility and disseminates them.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest
General Information | Course & Exam Schedules | Real-time Course & Classroom Status
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