EEE5541 Introduction to Digital Image and Video ProcessingBahçeşehir UniversityDegree Programs BUSINESS ADMINISTRATIONGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
BUSINESS ADMINISTRATION
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
Fall
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 : Dr. Öğr. Üyesi 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) Being able to identify problems and ask right questions
2) Having problem solving skills and developing necessary analytical attitude
3) Comprehending theoretical arguments along with counter arguments in detail
4) Gaining awareness of lifelong learning and being qualified for pursuing graduate education
5) Applying theoretical concepts in project planning
6) Communicating efficiently by accepting differences and carrying out compatible teamwork
7) Increasing efficiency rate in business environment
8) Developing innovative and creative solutions in face of uncertainty
9) Researching to gather information for understanding current threats and opportunities in business
10) Being aware of the effects of globalization on society and business while deciding
11) Possessing digital competence and utilizing necessary technology
12) Communicating in at least one foreign language in academic and daily life
13) Possessing managing skills and competence
14) Deciding with the awareness of the legal and ethical consequences of business operations
15) Expressing opinions that are built through critical thinking process in business and academic environment