GRADUATE SCHOOL

Ph.D. In Electrical-Electronics Engineering

EEE 501 | Course Introduction and Application Information

Course Name
Applied Digital Image Processing
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
EEE 501
Fall/Spring
3
0
3
7.5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Second Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives This course aims to teach the fundamental principles and techniques of digital image processing and their applications to engineering problems.The course covers topics such as point operations, image filtering and deconvolution, eigenimages, noise reduction and restoration, color image processing, multi-resolution processing, image compression, morphological image processing,scale-space techniques, feature extraction and recognition, image thresholding/segmentation, image registration and image matching, and software applications
Learning Outcomes The students who succeeded in this course;
  • know how to use the principles of image formation, sampling and quantization while analyzing image processing techniques and systems,
  • know how to use intensity transformations, spatial- and frequency-domain filtering techniques to process and enhance images,
  • know how to use specific techniques to restore images in the presence of different noise and degradation processes,
  • know how to apply the most common color models and use them in color image processing,
  • have knowledge of the advantages and limitations of different digital image processing algorithms,
  • be able to evaluate potential applications of digital image processing techniques,
  • be able to design and implement digital image processing algorithms using Matlab and image processing toolbox.
Course Description Image filtering and deconvolution, eigenimages, noise reduction and restoration, color image processing, multi-resolution processing, image compression, morphological image processing,scale-space techniques, feature extraction and recognition, image thresholding/segmentation, image registration and image matching.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction, Application Areas of Digital Image Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 1)
2 Digital Image Fundamentals. Sampling, Quantization, Aliasing, Moire patterns Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 2)
3 Point Operations,Image Intensity Transformations, Histogram Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 3)
4 Spatial Filtering, Image Enhancement in Spatial Domain Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 3)
5 Frequency Domain Filtering and Image Enhancement Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 4)
6 Image Restoration and Reconstruction Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 5)
7 Image Restoration and Reconstruction Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 5)
8 Midterm
9 Color Image Processing, Color Transformations
10 Multiresolution Image Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 6)
11 Image Compression Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch.7)
12 Morphological Image Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 9)
13 Image Segmentation and Registration Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 10)
14 In-class Presentations
15 In-class Presentations
16 Review of the Semester  

 

Course Notes/Textbooks The textbook referenced above and course slides
Suggested Readings/Materials Related Research Papers

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
-
-
Laboratory / Application
-
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
1
30
Presentation / Jury
Project
1
40
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
Total

Weighting of Semester Activities on the Final Grade
3
100
Weighting of End-of-Semester Activities on the Final Grade
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
16
3
48
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
1
20
20
Presentation / Jury
0
Project
1
89
89
Seminar / Workshop
0
Oral Exam
0
Midterms
1
20
20
Final Exam
0
    Total
225

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information. X
2 Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations. X
3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines. Knows and applies the research methods in studies of the area with a high level of skill.
X
4 Is informed about new and upcoming applications in the field and learns them whenever necessary. X
5 Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions. Can independently realize novel studies that bring innovation to the field, or methods, or design, or known methods.
X
6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs. X
7 Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process. Performs critical analysis, synthesis and evaluation of new and complex ideas. X
8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility. X
9 Engages in written and oral communication at least in Level C1 of the European Language Portfolio Global Scale. X
10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
X
11 Evaluates the results of scientific, technological and engineering research and development activities in terms of the social, environmental, health, safety and legal aspects. Examines social relations and norms related to the field, and develops and makes attempts to change them if necessary. Knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications.
X
12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics.
X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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