Information Package

Program of Computer Engineering (English)

CSE456

IMAGE PROCESSING

Course Code
CSE456
Semester
-
Theory+Practice
3 + 1
ECTS
5
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS5
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Know fundamental concepts about digital images.
  2. Determine the most suitable method and working space in the enhancement of the digital images.
  3. Know the characteristics of noise and apply the most suitable restoration technique.
  4. Determine and apply the most suitable segmentation algorithm with respect to the problem to be solved.
  5. Gain ability in application development
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionBasic concepts and definitons in image processing. Discrete time signals and systems. Frequency domain processing. Sampling, reproduction, quantization and rescaling. Image enhancement. Digital image demonstration. Image transformations and morphologic operations. Image improvement and restoration. Segmentation and description.
Course Contents
WEEK TOPICS
1st Week Introduction to Digital Image Processing
2nd Week Fundamental Concepts of Digital Image - I
3rd Week Fundamental Concepts of Digital Image - II
4th Week Gray-Level Transformations
5th Week Spatial Filtering - I
6th Week Spatial Filtering - II
7th Week Introduction to Frequency Domain
8th Week MIDTERM EXAM
9th Week Filtering in the Frequency Domain
10th Week Noise Models and Image Restoration - I
11th Week Image Restoration - II
12th Week Color Models and Transformations
13th Week Color Image Processing
14th Week Fundamentals of Image Segmentation
15th Week Image Segmentation Methods
Recommended or Required ReadingGonzalez Rafael C., Woods Richard E., Digital Image
Processing, 3/E, ISBN: 0-13-505267-X, Pearson Education,
2008.
Gonzalez Rafael C., Woods Richard E., Eddins Steven L.,
Digital Image Processing using MATLAB, 2/E, ISBN:
9780982085400, Pearson Education, 2009.
Planned Learning Activities and Teaching Methods
  • Experiment
  • Lecture
  • Questions/Answers
  • Problem Solving
  • Project
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 25
Assignment 3 15
Quiz 4 15
Attendance 1 5
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
Language of InstructionEnglish
Work Placement(s)No
LO1 LO2 LO3 LO4 LO5
K1 X
K2 X
K3 X
K4 X
K5 X
K6
K7
K8
K9
K10
K11