Course Details

DIGITAL IMAGE PROCESSING

COMP430

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Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
7COMP430DIGITAL IMAGE PROCESSING3+0+055

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program COMPUTER ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course To help students in understanding of foundations of Digital Image Processing (DIP)
To provide a broader view of common DIP problems
To introduce recent DIP based Computer Vision advancements
To show students implementation examples and tools
Course Content The principle objectives of this course are to provide an introduction to basic concepts and methodologies for digital image processing, and to develop a foundation that can be used as the basis for further study and research in this field. The course content includes, overview of digital image processing applications, transition of images from analog to digital domain and fundamentals of digital images, histogram processing, spatial filtering, discrete Fourier transform of one and two variables, and image filtering in frequency domain, various types of noises and their statistical properties, various filters for noise reduction, image enhancement, i.e., sharpening, softening etc. image reconstruction from projections, wavelets and multiresolution processing, image compression fundamentals, morphological image processing, image segmentation and thresholding.
Course Methods and Techniques Face-to-face
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Associate Prof.Dr. RİFAT KURBAN rifat.kurban@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Digital Image Processing (Rafael Gonzalez)
Digital Image Processing, R. C. Gonzalez, R. E. Woods, 3rd Edition, Prentice Hall, 2008
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Course Category
Mathematics and Basic Sciences %0
Engineering %100
Engineering Design %0
Social Sciences %0
Education %0
Science %0
Health %0
Field %0

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Ödev 3 % 40
Final examination 1 % 60
Total
4
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Ev Ödevi 3 20 60
Ders dışı çalışma 14 1 14
Yüz Yüze Ders 14 3 42
Final Sınavı 1 30 30
Total Work Load   Number of ECTS Credits 5 146

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Define the foundational concepts of Digital Image Processing (DIP).
2 Identify common problems in DIP.
3 Analyze various DIP techniques and compare their applications.
4 Apply appropriate DIP methods to solve image processing problems.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Digital Image Processing - -
2 Color and point operations - -
3 Spatial filtering - -
4 Frequency domain techniques 1 - -
5 Frequency domain techniques 2 - -
6 Image Pyramids - -
7 Edge detection - -
8 Image smoothing - -
9 Segmentation - -
10 Deep learning basics - -
11 Convolutional neural networks - -
12 Term project - -
13 Term project - -
14 Term project - -


Contribution of Learning Outcomes to Programme Outcomes
P1
All 4
C1 4
C2 4
C3 4
C4 4

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=74883&lang=en
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