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Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EEE5541	Introduction to Digital Image and Video Processing	Spring	3	0	3	12

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assist. Prof. ZAFER İŞCAN
Recommended Optional Program Components:	None
Course Objectives:	This is an introductory course on digital image and video processing designed for graduate students and senior level undergraduate students. The objectives of the course are as follows: To introduce the student to theoretical foundations in Digital Image and Video Processing; to introduce the student to modern applications in Digital Image and Video Processing; to give students a hands-on experience about image and video processing using extensive simulation assignments (mostly using MATLAB); to give students an ability to solve complex engineering problems, that require image and video processing.

Learning Outcomes

The students who have succeeded in this course;
1.Discuss the main processes and problems of image and video formation and reproduction
2.Describe image and video sampling and quantization.
3.Apply functions Image Processing Toolbox in MATLAB to image and video processing problems.
4.Define and compute apply geometric transformations on images.
5.Describe and apply gray level transformations and frequency domain filtering on images and video.
6.Discuss and apply image restoration, morphological image processing, and image segmentation
7.Apply basic image compression and feature extraction approaches.
8.Describe video sampling rate and standards conversion
9.Explain motion estimation, and video enhancement methods.

Course Content

Introduction and overview; Human Visual System,
Image Formation; Image Processing Basics; MATLAB Basics;
Image Processing Toolbox; Image Sensing and Acquisition;
Arithmetic and Logic Operators; Geometric Operators;
Gray-level Transformations; Histogram Processing;
Neighborhood Processing; Frequency Domain Filtering;
Image Restoration; Morphological Image Processing;
Edge Detection; Image Segmentation; Color Image Processing;
Image Compression and Coding; Feature Extraction and Representation, Visual Pattern Recognition; Video Fundamentals, Video Standards, Video Standards Conversion,
Motion Estimation and video enhancement

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction and overview, Human Visual System, Image Formation
2)	Image Processing Basics, MATLAB Basics
3)	MATLAB Image Processing Toolbox, Image Sensing and Acquisition
5)	Gray-level Transformations, Histogram Processing
7)	Edge Detection, Image Segmentation
8)	Image Segmentation, Midterm Exam
9)	Image Restoration, Morphological Image Processing
10)	Color Image Processing
11)	Image Compression and Coding
12)	Feature Extraction and Representation, Visual Pattern Recognition
13)	Video Fundamentals, Video Standards, Video Standards Conversion
14)	Motion Estimation and video enhancement

Sources

Course Notes / Textbooks:	Practical Image and Video Processing Using MATLAB, Oge Marques, Wiley, 2011, ISBN: 978111093467.
References:	Video Processing and Communications, by Yao Wang, Joern Ostermann, and Ya-Qin Zhang, Prentice Hall, 2002, ISBN 0-13-017547-1. Digital Video Processing, by M. Tekalp, Prentice Hall, 1995, ISBN 0-13-190075-7.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	4	% 20
Project	1	% 20
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	5	70
Project	1	14	14
Homework Assignments	4	20	80
Midterms	1	3	3
Final	1	3	3
Total Workload			212

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	To prepare students to become communication professionals by focusing on strategic thinking, professional writing, ethical practices, and the innovative use of both traditional and new media	2
2)	To be able to explain and define problems related to the relationship between facts and phenomena in areas such as Advertising, Persuasive Communication, and Brand Management
3)	To critically discuss and interpret theories, concepts, methods, tools, and ideas in the field of advertising
4)	To be able to follow and interpret innovations in the field of advertising
5)	To demonstrate a scientific perspective in line with the topics they are curious about in the field.
6)	To address and solve the needs and problems of the field through the developed scientific perspective
7)	To recognize and understand all the dynamics within the field of advertising
8)	To analyze and develop solutions to problems encountered in the practical field of advertising