ECTS - Digital Image Processing
Digital Image Processing (CMPE464) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Digital Image Processing | CMPE464 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| 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;
|
| 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 |
| 15 | Review | |
| 16 | Review |
Sources
| Course Book | 1. Gonzalez, R. C., Woods, R. E., Digital Image Processing, Addison-Wesley, 2008. |
|---|---|
| Other Sources | 2. Jain, A. K., Fundamentals of digital Image Processing, Prentice-Hall. |
| 3. Castleman, K. R., Digital Image Processing, Prentice Hall. | |
| 4. 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 advanced knowledge of computing and/or informatics to solve software engineering problems. | |||||
| 2 | Develop solutions using different technologies, software architectures and life-cycle approaches. | |||||
| 3 | An ability to design, implement and evaluate a software system, component, process or program by using modern techniques and engineering tools required for software engineering practices. | |||||
| 4 | An ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. | |||||
| 5 | Skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. | |||||
| 6 | An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain. | |||||
| 7 | An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 8 | Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies. | |||||
| 9 | An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 10 | Promote the development, adoption and sustained use of standards of excellence for software engineering practices. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 1 | 16 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| 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 | ||