Digital Image Processing (CMPE464) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Digital Image Processing CMPE464 3 0 0 3 5
Pre-requisite Course(s)
Course Language English
Course Type N/A
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 The main aim of the course is : to give an introduction to 1-D and 2-D signals, to give introduction to spatial domain and frequency domain of signals to give an introduction to theories and mathematical methods used in image analysis, to introduce the analytical tools and methods which are currently used in digital image processing, and to make the students to apply these tools in the laboratory in image restoration, enhancement and compression.
Course Learning Outcomes The students who succeeded in this course;
  • Develop theoretic and algorithmic principles behind the acquisition, display, manipulation and processing of digital images
  • Explain clearly the use of basic mathematical concepts in image analysis, in particular transform theory (in space as well as in the frequency domain), image enhancement methods, image compression and image restoration.
  • Provide development of skills to effectively integrate new concepts in image processing
Course Content Introduction to signal and image processing, introduction to digital image processing, sampling, reconstruction, and quantization, digital image representation, image transforms, enhancement, restoration, segmentation and description.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to signals and systems Other sources
2 1-D and 2-D Signals and signal processing Other source
3 Sampling and quantization of 2-D signals Other source
4 Introduction to Digital Images, and image processing applications Ch.1 (main text)
5 Fundamentals of image processing Ch.1-2 (main text)
6 Intensity Transformations and Spatial Filtering Ch. 2
7 Processing of 1-D and 2-D signals, and processing in the frequency domain, mathematical fundamentals of fast fourier transform Ch. 2
8 Image Enhancement Ch.3, Ch. 4
9 Image Restoration Ch.5
10 Color Image Processing Ch. 6
11 Image Compression Ch.8
12 Morphological Image Processing Ch.9
13 Image Segmentation Ch.10
14 Object Recognition. Ch.12


Course Book 1. Gonzalez, R. C., Woods, R. E., Digital Image Processing, Addison-Wesley, 2008.
Other Sources 2. 1. Jain, A. K., Fundamentals of digital Image Processing, Prentice-Hall.
3. 2. Castleman, K. R., Digital Image Processing, Prentice Hall.
4. 3. John G. Prokis and Dimitris G. Manolakis, “Digital Signal Processing: Principle, Algorithms and Applications” Prentice Hall Inc., Englewood Cliffs, NJ (USA), 3rd Ed., 1996.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 30
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 35
Toplam 7 100
Percentage of Semester Work 65
Percentage of Final Work 35
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 An ability to apply knowledge of mathematics, science, and engineering.
2 An ability to design and conduct experiments, as well as to analyse and interpret data.
3 An ability to design a system, component, or process to meet desired needs.
4 An ability to function on multi-disciplinary domains.
5 An ability to identify, formulate, and solve engineering problems.
6 An understanding of professional and ethical responsibility.
7 An ability to communicate effectively.
8 Recognition of the need for, and an ability to engage in life-long learning.
9 A knowledge of contemporary issues.
10 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
11 Skills in project management and recognition of international standards and methodologies
12 An ability to produce engineering products or prototypes that solve real-life problems.
13 Skills that contribute to professional knowledge.
14 An ability to make methodological scientific research.
15 An ability to produce, report and present an original or known scientific body of knowledge.
16 An ability to defend an originally produced idea.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Special Course Internship
Field Work
Study Hours Out of Class 16 1 16
Presentation/Seminar Prepration
Homework Assignments 5 8 40
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 129