İzmir Ekonomi Üniversitesi
  • TÜRKÇE

  • GRADUATE SCHOOL

    M.SC. in Electrical and Electronics Engineering (With Thesis)

    EEE 501 | Course Introduction and Application Information

    Course Name
    Applied Digital Image Processing
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    EEE 501
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s) -
    Course Objectives This course aims to teach the fundamental principles and techniques of digital image processing and their applications to engineering problems.The course covers topics such as point operations, image filtering and deconvolution, eigenimages, noise reduction and restoration, color image processing, multi-resolution processing, image compression, morphological image processing,scale-space techniques, feature extraction and recognition, image thresholding/segmentation, image registration and image matching, and software applications
    Learning Outcomes

    The students who succeeded in this course;

    • know how to use the principles of image formation, sampling and quantization while analyzing image processing techniques and systems,
    • know how to use intensity transformations, spatial- and frequency-domain filtering techniques to process and enhance images,
    • know how to use specific techniques to restore images in the presence of different noise and degradation processes,
    • know how to apply the most common color models and use them in color image processing,
    • have knowledge of the advantages and limitations of different digital image processing algorithms,
    • be able to evaluate potential applications of digital image processing techniques,
    • be able to design and implement digital image processing algorithms using Matlab and image processing toolbox.
    Course Description Image filtering and deconvolution, eigenimages, noise reduction and restoration, color image processing, multi-resolution processing, image compression, morphological image processing,scale-space techniques, feature extraction and recognition, image thresholding/segmentation, image registration and image matching.

     



    Course Category

    Core Courses
    Major Area Courses
    X
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Introduction, Application Areas of Digital Image Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 1)
    2 Digital Image Fundamentals. Sampling, Quantization, Aliasing, Moire patterns Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 2)
    3 Point Operations,Image Intensity Transformations, Histogram Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 3)
    4 Spatial Filtering, Image Enhancement in Spatial Domain Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 3)
    5 Frequency Domain Filtering and Image Enhancement Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 4)
    6 Image Restoration and Reconstruction Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 5)
    7 Image Restoration and Reconstruction Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 5)
    8 Midterm
    9 Color Image Processing, Color Transformations
    10 Multiresolution Image Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 6)
    11 Image Compression Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch.7)
    12 Morphological Image Processing Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 9)
    13 Image Segmentation and Registration Gonzales & Woods, Digital Image Processing, Prentice Hall,3rd ed., 2008 (Ch. 10)
    14 In-class Presentations
    15 In-class Presentations
    16 Review of the Semester  

     

    Course Notes/Textbooks The textbook referenced above and course slides
    Suggested Readings/Materials Related Research Papers

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    -
    -
    Laboratory / Application
    -
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    1
    30
    Presentation / Jury
    Project
    1
    40
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    30
    Final Exam
    Total

    Weighting of Semester Activities on the Final Grade
    3
    100
    Weighting of End-of-Semester Activities on the Final Grade
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    16
    3
    48
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    1
    20
    20
    Presentation / Jury
    0
    Project
    1
    89
    89
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    20
    20
    Final Exam
    0
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information
    -
    X
    -
    -
    -
    2 Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations
    -
    -
    X
    -
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines
    -
    -
    X
    -
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.

    -
    -
    X
    -
    -
    5 Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    X
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    -
    -
    X
    -
    -
    7 Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process.
    -
    -
    X
    -
    -
    8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
    -
    -
    X
    -
    -
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    -
    X
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    X
    -
    -
    -
    -
    11 Is knowledgeable about the social, environmental, health, security and law implications of Electrical and Electronics Engineering applications, knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications.
    X
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics.
    X
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


    NEW GÜZELBAHÇE CAMPUS

    Details

    GLOBAL CAREER

    As Izmir University of Economics transforms into a world-class university, it also raises successful young people with global competence.

    More..

    CONTRIBUTION TO SCIENCE

    Izmir University of Economics produces qualified knowledge and competent technologies.

    More..

    VALUING PEOPLE

    Izmir University of Economics sees producing social benefit as its reason for existence.

    More..

    BENEFIT TO SOCIETY

    Transferring 22 years of power and experience to social work…

    More..
    You are one step ahead with your graduate education at Izmir University of Economics.