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Syllabus ( CSE 564 )

   Basic information
Course title: Digital Image Processing
Course code: CSE 564
Lecturer: Prof. Dr. Yusuf Sinan AKGÜL
ECTS credits: 7.5
GTU credits: 3 (3+0+0)
Year, Semester: 1/2, Fall and Spring
Level of course: Second Cycle (Master's)
Type of course: Area Elective
Language of instruction: Turkish
Mode of delivery: Face to face , Lab work
Pre- and co-requisites: CSE 102
Professional practice: No
Purpose of the course: This course includes the methods and algorithms used for the acquisition, recording and processing of digital images, Students will comprehend the topics related to identification, usage and analysis of digital images. With the use of this knowledge, students wil be able to identify and solve real-world problems by designing problem specific algorithms.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. Identify how digital images are created in computer memory

    Contribution to Program Outcomes

    1. Define and manipulate advanced concepts of Computer Engineering
    2. Formulate and solve advanced engineering problems
    3. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
    4. Continuously develop their knowledge and skills in order to adapt to a rapidly developing technological environment,
    5. Find out new methods to improve his/her knowledge.

    Method of assessment

    1. Written exam
  2. Apply processing filters to images

    Contribution to Program Outcomes

    1. Define and manipulate advanced concepts of Computer Engineering
    2. Formulate and solve advanced engineering problems
    3. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
    4. Acquire scientific knowledge
    5. Design and conduct research projects independently

    Method of assessment

    1. Homework assignment
  3. List image compression methods

    Contribution to Program Outcomes

    1. Define and manipulate advanced concepts of Computer Engineering
    2. Formulate and solve advanced engineering problems
    3. Use advanced knowledge of mathematics, science, and engineering
    4. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
    5. Acquire scientific knowledge
    6. Design and conduct research projects independently

    Method of assessment

    1. Written exam
   Contents Up
Week 1: Overview, Computer imaging systems
Week 2: Image analysis, preprocessing
Week 3: Human visual system, image model
Week 4: Image enhancement, gray scale mods, histogram mod
Week 5: Discrete transforms, fourier
Week 6: Discrete cosine, walsh-hadamard, Haar, PCT, filtering
Week 7: Midterm exam
Week 8: Filtering, wavelet transform, pseudocolor
Week 9: Image enhancement, sharpening, smoothing
Week 10: Image restoration, overview, system model, noise
Week 11: Geometric transforms
Week 12: Image compression: system model, lossless methods
Week 13: Image compression: lossy methods
Week 14: Image compression: lossy methods
Week 15*: Image compression: lossy methods
Week 16*: Final exam
Textbooks and materials: Multidimensional Signal, Image and Video Processing and Coding by John W. Woods, Elsevier 2006.
Recommended readings: Digital Image Processing and Analysis, 2nd Edition , Scott E Umbaugh, The CRC Press, Boca Raton, FL, January 2011
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 7 30
Other in-term studies: 0
Project: 0
Homework: 2-10 30
Quiz: 0
Final exam: 16 40
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 3 14
Own studies outside class: 3 14
Practice, Recitation: 0 0
Homework: 8 10
Term project: 0 0
Term project presentation: 0 0
Quiz: 0 0
Own study for mid-term exam: 10 1
Mid-term: 1 1
Personal studies for final exam: 10 1
Final exam: 2 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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