CE 490 | 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
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives This course introduces the fundamental principles and algorithms of digital image processing systems. The course will cover many subjects including image sampling and quantization; spatial and frequency domain image enhancement techniques; digital signal processing theories used for digital image processing, such as onedimensional and twodimensional convolution, and twodimensional Fourier transformation; color models and basic color image processing.
Course Description The students who succeeded in this course;
  • will be able to process images using techniques of smoothing, sharpening, histogram processing, and filtering,
  • will be able to explain sampling and quantization processes in obtaining digital images from continuously sensed data,
  • will be able to enhance digital images using filtering techniques in the spatial domain,
  • will be able to enhance digital images using filtering techniques in the frequency domain,
  • will be able to restore images in the presence of only noise through filtering techniques,
  • will be able to describe most commonly applied color models and their use in basic color image processing,
  • will be able to write Matlab codes using image processing toolbox.
Course Content The following topics will be included: Digital images as twodimensional signals; twodimensional convolution, Fourier transform, and discrete cosine transform; Image processing basics; Image enhancement; Image restoration; Wavelets and Multiresolution processing; Image coding and compression.

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction. What is Digital Image Processing? Application areas of digital image processing Chapter 1. Sections 1.1-1.3. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
2 Digital Image Fundamentals. How digital images are generated? Sampling, quantization, aliasing, Moire patterns, image zooming and shrinking Chapter 1-2. Sections 1.4,1.5, 2.1-2.4. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
3 Digital Image Fundamentals. How digital images are generated? Sampling, quantization, aliasing, Moire patterns, image zooming and shrinking Chapter 1-2. Sections 1.4,1.5, 2.1-2.4. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
4 Human visual system Chapter 2. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
5 Image Enhancement in the spatial domain. Basic gray level transformations. Smoothing and sharpening spatial filters. Chapter 3. Sections 3.1-3.6. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
6 Image Enhancement in the spatial domain. Histogram processing. Chapter 3. Sections 3.1-3.6. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
7 The 2D Discrete Fourier Transform and Its Inverse, Properties of the 2D DFT and the 2D Convolution Theorem Chapter 4. Sections 4.5.5, 4.6. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
8 The 2D Discrete Fourier Transform and Its Inverse, Properties of the 2D DFT and the 2D Convolution Theorem Chapter 4. Sections 4.5.5, 4.6. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
9 Mid-term Exam Chapter 4. Sections 4.74.10. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
10 Image Enhancement in the frequency domain. Chapter 4. Sections 4.7-4.10. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
11 Image Enhancement in the frequency domain. Chapter 4. Sections 4.7-4.10. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
12 Image restoration: system model, noise model, estimation of degradation function. Chapter 5. Sections 5.1,5.2,5.7-5.10. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
13 Image restoration in the presence of noise only, inverse filtering, minimum mean square error (Wiener) filtering. Chapter 5. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
14 Color Image Processing. Color transformations. Color image smoothing and sharpening Chapter 6. Section 6.1-6.6. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
15 Color Image Processing. Color transformations. Color image smoothing and sharpening Chapter 6. Section 6.1-6.6. Digital Image Processing. Gonzalez & Woods. ISBN 013168728X
16 Review of the semester

 

Course Notes/Textbooks R. C. Gonzalez and R. E. Woods, “Digital Image Processing”, PrenticeHall, 3rd Ed., 2008, ISBN 013168728X.
Suggested Readings/Materials R. C. Gonzalez, R. E. Woods, S. L. Eddins, “Digital Image Processing Using MATLAB”, PrenticeHall, 2nd Ed., 2009, ISBN 9780982085400.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
-
-
Laboratory / Application
1
20
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
2
40
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
Theoretical 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
15
3
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
2
15
Final Exam
1
27
    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, Computer Science and Software 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 Software Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design, implement, verify, validate, document, measure and maintain a complex software system, process, or product under realistic constraints and conditions, in such a way as to meet the requirements; ability to apply modern 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 software engineering applications; to be able to use information technologies effectively.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex Software Engineering problems.

X
6

To be able to work effectively in Software Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

X
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 be able to present effectively, to be able to give and receive clear and comprehensible instructions.

8

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

9

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

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 Software Engineering, and to be able to communicate with colleagues in a foreign language.

X
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 Software Engineering.

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