COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Introduction to Digital Image Processing
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
CE 490
Fall/Spring
3
0
3
5
Prerequisites
  To be a junior (3th year) student
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Problem Solving
Simulation
Application: Experiment / Laboratory / Workshop
Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives This course introduces the fundamental principles and algorithms of digital image processing systems. The course covers image sampling and quantization; spatial and frequency domain image enhancement techniques; signal processing theories used for digital image processing, such as one- and two-dimensional convolution, and two-dimensional Fourier transformation; morphological image processing; color models and basic color image processing.
Learning Outcomes The students who succeeded in this course;
  • Explain digital images and the sampling and quantization processes used to obtain them.
  • Use histogram based techniques for digital image processing.
  • Apply spatial or frequency domain processing and filtering techniques to smooth and sharpen digital images.
  • Utilize filtering techniques to restore images in the presence of noise.
  • Describe morphological image processing techniques.
  • Explain commonly used color models and their applications in basic color image processing.
  • Apply digital image processing methods to practical problems.
Course Description The course content includes: Digital images as two-dimensional signals; two-dimensional convolution, Fourier transform, and discrete cosine transform; Image processing basics; Image enhancement; Image restoration; Image coding and compression.
Related Sustainable Development Goals

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction Chapter 1. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
2 Fundamentals of digital images Chapter 2. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
3 Global histogram processing Chapter 3. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
4 Local histogram processing Chapter 3. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
5 Point processing, basic gray-level transformations Chapter 3. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
6 Spatial filtering, convolution, smoothing filters Chapter 3. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
7 Spatial filtering, convolution, sharpening filters, combining spatial filtering techniques Chapter 3. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
8 Filtering in the frequency domain, convolution theorem Chapter 4. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
9 Midterm Exam
10 Image restoration for noise removal Chapter 5. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
11 Morphological image processing Chapter 9. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
12 Color image processing Chapter 6. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
13 Fundamentals of image compression, JPEG image compression algorithm Chapter 8. Digital Image Processing. Gonzalez & Woods. ISBN 978-0-13-234563-7
14 Project presentations
15 Project presentations
16 Final Exam
Course Notes/Textbooks

R. C. Gonzalez, R. E. Woods, Digital Image Processing, Pearson, 2010, 3/E, ISBN: 978-0-13-234563-7

Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weighting
Participation
Laboratory / Application
-
-
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
10
Project
1
20
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
3
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
14
2
28
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
4
Project
1
30
Seminar / Workshop
Oral Exam
Midterms
1
15
Final Exams
1
25
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Electrical and Electronics Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

X
2

To be able to identify, define, formulate, and solve complex Electrical and Electronics Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

X
4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Electrical and Electronics Engineering applications; uses computer and information technologies effectively.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Electrical and Electronics Engineering research topics.

X
6

To be able to work efficiently in Electrical and Electronics Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

X
8

To have knowledge about global and social impact of engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to Electrical and Electronics Engineering; to be aware of the legal ramifications of Electrical and Electronics Engineering solutions.

X
9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications

X
10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Electrical and Electronics Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1)

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Electrical and Electronics Engineering.

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