1	Course Title:	DIGITAL IMAGE PROCESSING
2	Course Code:	BMB4013
3	Type of Course:	Optional
4	Level of Course:	First Cycle
5	Year of Study:	4
6	Semester:	7
7	ECTS Credits Allocated:	5
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. Ahmet Emir DİRİK
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:
18	Website:
19	Objective of the Course:	The main objectives of the course are as follows: To provide essential knowledge of image processing fundamentals. To develop advanced practical skills and competency in image processing. To apply these skills to the full spectrum of image processing applications, through independent research and investigation.
20	Contribution of the Course to Professional Development	To be able to follow innovations and apply them in the field by using the competence of collecting information, researching and analyzing them.

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Learning Outcomes:

1 Gain sufficient knowledge on image processing; the ability to model and solve computer vision application problems using theoretical and practical knowledge. ; ; 2 Gain the ability to identify, model, and solve complex problems; the ability to select and apply appropriate analysis and modeling methods for these problems. ; ;

22	Course Content:

Week	Theoretical	Practical
1	Overview, Computer imaging systems
2	Image analysis, preprocessing
3	Human visual system, image model
4	Image enhancement, gray scale mods, histogram mod
5	Discrete transforms, Fourier
6	discrete cosine, Walsh-Hadamard, Haar, PCT, filtering
7	filtering, wavelet transform, pseudocolor
8	Image enhancement, sharpening, smoothing
9	Image restoration, overview, system model, noise removal: order filters
10	Image restoration: noise removal: mean & adaptive filters, degradation model, inverse filter
11	Freq. filters
12	geometric transforms
13	image compression: system model, lossless methods
14	image compression: lossy methods

23	Textbooks, References and/or Other Materials:	Digital Image Processing, Rafael Gonzalez, 2nd edition Addison-Wesley
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	40
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	60
Total	2	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Measurement and evaluation is carried out according to the principles of Bursa Uludag University Associate and Undergraduate Education Regulation.
Information

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ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	3	42
Practicals/Labs	0	0	0
Self Study and Preparation	14	2	28
Homeworks, Performances	0	0	0
Projects	1	30	30
Field Studies	0	0	0
Midtermexams	1	18	18
Others	0	0	0
Final Exams	1	32	32
Total WorkLoad			168
Total workload/ 30 hr			5
ECTS Credit of the Course			5

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 LO1 5 0 0 0 0 0 0 0 0 0 0 0 LO2 0 5 0 0 0 0 0 0 0 0 0 0

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High