INTERNATIONAL BURCH UNIVERSITY
Graduate Study - Faculty of Engineering and Natural Sciences
3+2 Information Technology Master
2013-2014

SYLLABUS
Code Name Level Year Semester
CEN 557 Digital Image Processing Graduate 1 Spring
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
7.5 49

Instructor Assistant Coordinator
Ercan Gökgöz, PhD, Research Assistant Elmedin Selmanović, Assist. Prof. Dr.
[email protected] no email

COURSE OBJECTIVE
Visual information plays an important role in many aspects of our life. Much of this information is represented by digital images. Digital image processing found many applications including television, tomography, photography, printing, robot perception, and remote sensing. This is an introductory course to the fundamentals of digital image processing. It emphasizes general principles of image processing, rather than specific applications. The following topics will be covered: image acquisition and display, colour representations, image sampling and quantization, point operations, linear image filtering and correlation, image transforms and sub-band decompositions, contrast and colour enhancement, image restoration, and image compression.

COURSE CONTENT
Week
Topic
  1. Introduction to Digital Image Processing (DIP)
  2. Digital Image Fundamentals
  3. Intensity Transformations and Spatial Filtering I
  4. Intensity Transformations and Spatial Filtering II
  5. Intensity Transformations and Spatial Filtering III
  6. Filtering in Frequency Domain I
  7. Filtering in Frequency Domain II
  8. MIDTERM EXAM
  9. Filtering in Frequency Domain III
  10. Image Restoration and Reconstruction I
  11. Image Restoration and Reconstruction II
  12. Colour Image Processing
  13. Image Compression
  14. Morphological Image Processing

LABORATORY/PRACTICE PLAN
Week
Topic

    TEACHING/ASSESSMENT
    Description
    • Lectures
    • Practical Sessions
    • Project
    • Assignments
    Description (%)
    Method Quantity Percentage (%)
    Project560
    Midterm Exam(s)115
    Final Exam125
    Total: 100
    Learning outcomes
    • Process images using techniques of smoothing, sharpening, histogram processing, and filtering
    • Explain sampling and quantization processes in obtaining digital images from continuously sensed data
    • Enhance digital images using filtering techniques in the spatial and frequency domain
    • Restore images in the presence of only noise through filtering techniques
    • Explain most commonly applied colour models and their use in basic colour image processing
    TEXTBOOK(S)
    • R. C. Gonzalez and R. E. Woods, “Digital Image Processing”, 3rd Ed., 2008

    ECTS (Allocated based on student) WORKLOAD
    Activities Quantity Duration (Hour) Total Work Load
    Lecture (14 weeks x Lecture hours per week)45145
    Laboratory / Practice (14 weeks x Laboratory/Practice hours per week) 0
    Midterm Examination (1 week)122
    Final Examination(1 week)122
    Preparation for Midterm Examination 0
    Preparation for Final Examination7.50
    Total Workload: 49
    ECTS Credit (Total workload/25): 2