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  Course Description
Course Name : Digital Image Processing

Course Code : EE-622

Course Type : Optional

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Asst.Prof.Dr. SAMİ ARICA

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

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : This course introduces the fundamental concepts and methods of image processing and analysis.

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

Language of Instruction : English

Work Place : Department of Electrical and Electronics engineering building classrooms.


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Introduction, image representations. Textbook reading/Problem solving. Lecture.
2 Image Enhancement in Spatial Domain. Histogram Transformation. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
3 Image Enhancement in Spatial Domain. Histogram Transformation (continued). Assigment I. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
4 Noise Reduction. Assigment II. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
5 Image enhancement in frequency domain. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
6 mage enhancement in frequency domain (continued). Assigment III. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
7 Image restoration. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
8 Midterm Exam. Textbook reading/Problem solving/Computer application. Written exam.
9 Image restoration (continued). Assigment IV. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
10 Color image processing. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
11 Color image processing (continued). Assigment V. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
12 Image segmentation. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
13 Image segmentation (continued). Assigment VI. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
14 Image compression. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
15 Image compression (continued). Assigment VII. Textbook reading/Problem solving/Computer application. Lecture/Computer application.
16/17 Final exam. Textbook reading/Problem solving/Computer application. Written exam.


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  Digital Image Processing. Bernd Jahne. 2005. Springer-Verlag.
 Fundamentals of Digital Image Processing. Anil K. Jain. 1989. Prentice Hall
 Digital Image Processing. 2nd Edition. Gonzalez and Woods. 2002. Prentice Hall.
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 50
    Homeworks/Projects/Others 14 50
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Communicates with people in an appropriate language and style. 2
2 Specializes by furthering his knowledge level at least in one of the basic subfields of electiral-electronic engineering. 5
3 Grasps the integrity formed by the topics involved in the field of specialization. 5
4 Grasps and follows the existing literature in the field of specialization. 4
5 Comprehends the interdisciplinary interaction of his field with other fields. 5
6 Has the aptitude to pursue theoretical and experimental work. 5
7 Forms a scientific text by compiling the knowledge obtained from research. 3
8 Works in a programmed manner within the framework set by the advisor on the thesis topic, in accordance with the logical integrity required by this topic. 4
9 Performs a literature search in scientific databases; in particular, to scan the databases in an appropriate manner, to list and categorize the listed items. 3
10 Has English capability at a level adequate to read and understand a scientific text in his field of specialization, written in English. 4
11 Compiles his/her knowledge in his/her field of specialization. in a presentation format, and presents in a clear and effective way. 4
12 Writes a computer code aimed at a specific purpose, in general, and related with his/her field of specialization, in particular 5
13 Pursues research ın new topics based on his/her existing research experıence. 3
14 Gives guidance in environments where problems related with his/her field need to be solved, and takes initiative. 4
15 Develops and evaluates projects, policies and processes in his field of specialization. 2
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 16 3 48
Assesment Related Works
    Homeworks, Projects, Others 14 4 56
    Mid-term Exams (Written, Oral, etc.) 1 2 2
    Final Exam 1 2 2
Total Workload: 150
Total Workload / 25 (h): 6
ECTS Credit: 6