EE622 Digital Image Processing

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code EE622
Name Digital Image Processing
Term 2023-2024 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language İngilizce
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. SAMİ ARICA


Course Goal / Objective

This course introduces the fundamental concepts and methods of image processing and analysis.

Course Content

Mathematical representation of images. Image enhancement. Image restoration. Color image processing. Image segmentation. Image compression.

Course Precondition

There are no prerequisites for the course.

Resources

Digital Image Processing. 2nd Edition. Gonzalez and Woods. 2002. Prentice Hall. Fundamentals of Digital Image Processing. Anil K. Jain. 1989. Prentice Hall

Notes

No suggested additional course notes.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Analyzes general terminology of digital image processing.
LO02 Examines various types of images, intensity transformations and spatial filtering.
LO03 Develops Fourier transform for image processing in frequency domain.
LO04 Evaluates the methodologies for image segmentation, restoration, topology, etc.
LO05 Implements image process and analysis algorithms.
LO06 Applies image processing algorithms in practical applications.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Being able to specialize in at least one of the branches that form the foundations of electrical-electronic engineering by increasing the level of knowledge beyond the undergraduate level. 5
PLO02 Bilgi - Kuramsal, Olgusal To comprehend the integrity of all the subjects included in the field of specialization. 5
PLO03 Bilgi - Kuramsal, Olgusal Knowing and following the current scientific literature in the field of specialization 5
PLO04 Bilgi - Kuramsal, Olgusal To be able to comprehend the interdisciplinary interaction of the field with other related branches. 5
PLO05 Bilgi - Kuramsal, Olgusal Ability to do theoretical and experimental work 4
PLO06 Bilgi - Kuramsal, Olgusal To create a complete scientific text by compiling the information obtained from the research.
PLO07 Bilgi - Kuramsal, Olgusal To work on the thesis topic programmatically, following the logical integrity required by the subject within the framework determined by the advisor. 4
PLO08 Bilgi - Kuramsal, Olgusal To search for literature in scientific databases, particularly the ability to correctly and accurately scan databases and evaluate and categorize listed items. 4
PLO09 Bilgi - Kuramsal, Olgusal Knowledge of English at a level that can easily read and understand a scientific text written in English in the field of specialization
PLO10 Bilgi - Kuramsal, Olgusal Compile information on his/her expertise in a presentation format and present it understandably and effectively.
PLO11 Bilgi - Kuramsal, Olgusal Ability to write a computer program in a familiar programming language, generally for a specific purpose, specifically related to the field of expertise. 4
PLO12 Bilgi - Kuramsal, Olgusal Being able to guide and take the initiative in environments that require solving problems related to the field
PLO13 Yetkinlikler - İletişim ve Sosyal Yetkinlik Ability to communicate with people in an appropriate language
PLO14 Yetkinlikler - Öğrenme Yetkinliği To be able to produce projects, policies, and processes in the field of expertise and to evaluate these elements 4
PLO15 Yetkinlikler - Öğrenme Yetkinliği Ability to research new topics based on existing research experience 4


Week Plan

Week Topic Preparation Methods
1 Introduction, image representations. Textbook reading/Problem solving. Öğretim Yöntemleri:
Anlatım
2 Image Enhancement in Spatial Domain. Histogram Transformation. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
3 Image Enhancement in Spatial Domain. Histogram Transformation (continued). Assigment I. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
4 Noise Reduction. Assigment II. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
5 Image enhancement in frequency domain. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
6 Image enhancement in frequency domain (continued). Assigment III. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
7 Image restoration. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
8 Mid-Term Exam Textbook reading/Problem solving/Computer application. Ölçme Yöntemleri:
Yazılı Sınav
9 Image restoration (continued). Assigment IV. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
10 Color image processing. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
11 Color image processing (continued). Assigment V. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
12 Image segmentation. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
13 Image segmentation (continued). Assigment VI. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
14 Image compression. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
15 Image compression (continued). Assigment VII. Textbook reading/Problem solving/Computer application. Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
16 Term Exams Textbook reading/Problem solving. Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Textbook reading/Problem solving. Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 6 84
Assesment Related Works
Homeworks, Projects, Others 7 4 28
Mid-term Exams (Written, Oral, etc.) 1 2 2
Final Exam 1 2 2
Total Workload (Hour) 158
Total Workload / 25 (h) 6,32
ECTS 6 ECTS

Update Time: 08.05.2023 11:27