ÇAĞ UNIVERSITY
FACULTY OF ARTS AND SCIENCES
Learning Outcomes
of the Course
Code
Course Title
Credit
ECTS
MAT 492
Digital Image Processing
3 (3-0)
5
Prerequisites
None
Language of Instruction
Mode of Delivery
Face to face
English
Type and Level of Course
Elective / 4.Year/ Spring Semester
Lecturers
Name(s)
Contacts
Lecture Hours
Office Hours
Course Coordinator Assist.Prof.Dr. M. Fatih
mfakay@cu.edu.tr
AKAY
Course Objective
Matlab is the premier software package for technical computation, data analysis, and
visualization in education and industry. Students will be able to evaluate the fundamentals
and techniques of image processing using MATLAB and the Image Processing Toolbox.
The course describes the types of images and it also explains the basics of working with
image data and coordinate systems.
Relationship
Students who have completed the course successfully should
be able to
Net Effect
Prog. Output
1
do simple and complex calculation using Matlab
7 & 3 &9
4 & 2 &5
2
use the Matlab programming environment
7 & 3 &9
4&2&5
3
develop an overview of the field of image processing.
3
3
4
comprehend the fundamental algorithms and how to implement
3&9
3&5
them.
5
gain experience in applying image processing algorithms to real
7&3&9
2 & 3 &1
problems.
Course Description: The course will focus on the design and development of Matlab programming and image
processing. It provides a comprehensive theory of various image processing tasks and the practical experience to
simulate them. Upon the completion of this course, the students will have gained a hands-on experience about the below
topics through extensive simulation assignments.
Course Contents:( Weekly Lecture Plan )
Weeks
Topics
Preparation
Teaching Methods
1
Lectures and Demonstration
Introduction to Matlab
Textbook 1 Ch.1
2
Lectures and Demonstration
Arrays, Polynomial Operations Using Arrays,
Textbook 1 Ch.2
Functions & Files
3
Lectures and Demonstration
Advanced Function Programming, Working
Textbook 1 Ch.3
with Data Files
4
Image Processing- Vector Graphics
Lectures and Demonstration
Textbook 1 Ch.9
5
Lectures and Demonstration
Morphological Image Processing
Textbook 1 Ch.9
6
Digital Image Fundamentals: Sampling and
Lectures and Demonstration
Textbook 2 Ch. 1 & 2
Fourier analysis
7
Lectures and Demonstration
Intensity
Transformations
and
Spatial
Textbook 2 Ch.3
Filtering: Histogram Processing
8
Lectures and Demonstration
Intensity
Transformations
and
Spatial
Textbook 2 Ch.3
Filtering: Spatial Filtering
9
Lectures and Demonstration
Filtering in the Frequency Domain:
Textbook 2 Ch.4
 Preliminary Concepts
 Extension to functions of two variables
10
Lectures and Demonstration
Filtering in the Frequency Domain:
Textbook 2 Ch.4
 Image Smoothing
 Image Sharpening
11
Lectures and Demonstration
Image Restoration and Reconstruction
Textbook 2 Ch.5
 Noise Models
 Noise Reduction
12
Lectures and Demonstration
Image Restoration and Reconstruction:
Textbook 2 Ch.5
 Inverse Filtering
 MMSE (Wiener) Filtering
13
Lectures and Demonstration
Color Image Processing:
Textbook 2 Ch.6
 Color Models
14
 Color Transforms
Color Image Processing:
Image Segmentation Based on color
Textbook
Activities
Midterm Exam
Effect of The Activities
Effect of The Final Exam
Lectures and Demonstration
Textbook 2 Ch.6
REFERENCES
1. Palm, W.J., Introduction to Matlab 7 for Engineers, McGraw Hill, 2005
2. Gonzalez, R.C., Woods, R.E., Eddins, S.L., Digital Image Processing Using MATLAB,
Prentice-Hall, 2003.
Number
1
Contents
Hours in Classroom (Face-to-face)
Hours out Classroom
Midterm Exam
Final Exam
ASSESSMENT METHODS
Effect
40%
40%
60%
ECTS TABLE
Number
14
14
1
1
Notes
Hours
4
4
12
25
Total
Total / 30
ECTS Credit
RECENT PERFORMANCE
Total
56
56
12
25
149
=149/30=4.9
5