Ondokuz Mayıs Üniversitesi Bilgi Paketi - Ders Kataloğu

Description of Individual Course Units

Course Unit CodeCourse Unit TitleType of CourseYearSemesterECTS
HRT313 Digital Image Processing 927006 3 5 3
Level of Course Unit
First Cycle
Objectives of the Course
Instructing the basic image processing approaches with a content that enables these approaches be used easily in photogrammetry and remote sensing fields.
Name of Lecturer(s)
Doç.Dr. Erdem Emin Maraş
Learning Outcomes
  1. Learns the mathematical expression of images and the data structures of the digital images.
  2. The student learns the nature of the digital images.
  3. Understands the existence and the organization of the geometric and the semantic data and the relations between them in digital images.
  4. Develops image processing software
  5. Learns the methods to be used to correct the radiometric errors of the images.
  6. Applies the instructed methods by writing his/her own program functions to solve the problems which use images.
  7. It develops and develops information for data structures, algorithms, numerical analysis and linear algebra for computer programs to develop.
  8. Understands the power and importance of the visual data and their value in technological developments.
Mode of Delivery
Formal Education
Prerequisites and co-requisities
Recommended Optional Programme Components
Recommended or Required Reading
Gonzalez R., 1987. Digital Image Processing, Addison Wesley Publishing, USA.Other image processing text-books.
Planned Learning Activities and Teaching Methods
Language of Instruction
Work Placement(s)
Course Contents
Basics of the image processing, structure of digital images, imaging techniques, mathematical expression of imaged, image transformations, image enhancement techniques, image restoration, image segmentation, image compression techniques.
Weekly Detailed Course Contents
Week Theoretical Practice Laboratory
1.Introduction to digital image processing: basic concepts and definitions.
2.Physical principles of image sensing: geometric and radiometric sampling.
3.Color spaces and color transformations.
4.Neighbourhood and connectedness relations of pixels. Image as a matrix.
5.Image data coding and file formats.
6.Overview of the prograaming techniques that may be used to process the image data.
7.Noise in images, spatial filters.
8.Gradient in images. Edge filters and image segmentation.
9.Image enhancement techniques. Image histogram and statistical interpretation of images.
10.Mid-term exam.
11.Histogram transformation and modification techniques.
12.Geometric image transformations and resmpling the pixel values.
13.Use of texture data in image processing.
14.Corelation concepts and image matching techniques.
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight (%)
Midterm Examination150
End Of Term (or Year) Learning ActivitiesQuantityWeight (%)
Final Examination1100
Term (or Year) Learning Activities40
End Of Term (or Year) Learning Activities60
Workload Calculation
ActivitiesQuantityTime(hours)Total Workload(hours)
Midterm Examination122
Final Examination122
Attending Lectures14228