TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	5
NAME OF LECTURER(S)	Associate Professor Emre Sümer Assistant Professor Hakan Tora
LEARNING OUTCOMES OF THE COURSE UNIT	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 DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Basic 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 Digital Image Fundamentals - I 3rd Week Digital Image Fundamentals - II 4th Week Intensity Transformations 5th Week Spatial Filtering 6th Week Frequency Domain Background 7th Week Filtering in the Frequency Domain 8th Week Midterm 9th Week Noise Models and Image Restoration - I 10th Week Image Restoration - II 11th Week Color Models and Transformations 12th Week Color Image Processing 13th Week Image Segmentation Fundamentals 14th Week Image Segmentation Methods
RECOMENDED OR REQUIRED READING	Gonzalez 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
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 1,5 1,5 Preparation for Quiz 4 1 4 Individual or group work Preparation for Final exam 1 30 30 Course hours 14 4 56 Preparation for Midterm exam 1 20 20 Laboratory (including preparation) Final exam 1 2 2 Homework 3 10 30 Quiz 4 ,5 2 Total Workload 145,5 Total Workload / 30 4,85 ECTS Credits of the Course 5
LANGUAGE OF INSTRUCTION
WORK PLACEMENT(S)	No