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)
N/A

Course Language	English
Course Type	N/A
Course Level	Bachelor’s Degree (First Cycle)
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

Sources

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
#	Program Qualifications / Competencies	1	2	3	4	5
1	Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area
2	Can apply gained knowledge and problem solving abilities in inter-disciplinary research
3	Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary
4	Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study
5	Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework					X
6	Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility
7	Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation
8	To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2)
9	Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge
10	Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach.
11	Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

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