COURSE UNIT TITLE

: TRANSFORM BASED IMAGE PROCESSING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSE 6009 TRANSFORM BASED IMAGE PROCESSING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR DERYA BIRANT

Offered to

Computer Engineering (English)
Computer Engineering (English)
COMPUTER ENGINEERING (ENGLISH)

Course Objective

The course is meant to give a detailed view to the field of Digital Image Processing as well as to the high order mathematics required to be able to deal with utilized. It is aimed to get acquainted to the concepts such as Discrete Fourier Transform, Discrete Cosine Transform, and Wavelet Transform .

Learning Outcomes of the Course Unit

1   Identify image processing problems
2   Describe and assess mathematical solutions to classical image processing problems
3   Explain advanced computer image processing/analysis and interpretation algorithms and methods.
4   Design, implement and describe methods for solving advanced image processing/analysis problems.
5   Apply the relevant underlying concepts and principles for image processing/analysis and interpretation

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Image Processing
2 Review of Linear Algebra
3 Vector Spaces, Inner Products
4 Signal Representation by Orthogonal Bases
5 Fourier Transform
6 Discrete Fourier Transform and its Application To Image Processing
7 The Discrete Sine and Cosine Transform
8 The Discrete Sine and Cosine Transform
9 The Walsh-Hadamard Transform
10 Haar Transform
11 Karhunen-Loeve Transform, Principal Component Analysis
12 Wavelet Transforms
13 Image Processing Applications
14 Image Processing Applications

Recomended or Required Reading

Textbook: Gonzalez R. C., Woods R. E., (2008), Digital Image Processing , 3rd Edition, Prentice Hall
Supplementary Book: Lim J. S., (1990), Two-Dimensional Signal and Image Processing , Prentice Hall.

Planned Learning Activities and Teaching Methods

Presentations, term projects, paper research and examination

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 PRJ PROJECT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE PRJ * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) PRJ * 0.30 + MTE * 0.30 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Learning Outcomes (LO) 1, 2, 3, 4, and 5 will be assessed by examination. LOs 2, 3, 4, and 5 will also be assessed by Projects.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Dr. Özlem ÖZTÜRK
Dokuz Eylul University
Department of Computer Engineering
Tinaztepe Campus 35160 BUCA/IZMIR
Tel: +90 (232) 301 74 17
e-mail: ozlem.ozturk@cs.deu.edu.tr

Office Hours

Friday 9:00 12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation for midterm exam 1 6 6
Preparation for final exam 1 8 8
Design Project 2 26 52
Preparations before/after weekly lectures 14 4 56
Preparing presentations 2 10 20
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 188

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.133233323222
LO.233233323222
LO.333233323222
LO.433233323222
LO.533233323222