Image Processing (Theory)

Module Information

Module Semester:
Module Part:
Sub-Module Code:
Hours per Week:
Module ECTS Credits:
Available to ERASMUS Students:
Module Staff:

Module Objective

The aim of this course is to familiarize students with the implementation in Matlab of the basic techniques for handling images and developing algorithms for image processing (quality enhancement, restoration, coding, compression).

Module Study Targets

Upon completion of the course, students will have the ability to:

  • Describe the theory and principles of image and video processing techniques
  • Illustrate the theory and principles of image and video processing techniques
  • Definealgorithms for image enhancement and restoration
  • Identify image transformations
  • Produce image transformations
  • Define image coding and compression techniques
  • Propose image coding
  • Select the appropriate compression technique
  • Design software using MATLAB

Module Acquired Abilities

  • Decision Making: Synthesis of techniques for composite problems
  • Autonomous work: Knowledge of development tools
  • Teamwork: Ability for dialog and cooperation for the development of composite algorithms
  • Work in a multidisciplinary environment: Ability perception problems and needs as well as ability for analysis and proposals synthesis

Module Description

The theoretical part consists of the following topics:

  1. Introduction to image processing principles
  2. Image Enhancement
  3. Image Restoration
  4. Image Morphology
  5. Sampling and Quantization
  6. Image Transforms
  7. Fourier Transform
  8. DCT Transform
  9. Image Coding (Selective chapters)
  10. Image Compression
  11. JPEG standard
  12. Video coding (Selective chapters)

Module Student Evaluation

Written examination: 60%

Laboratory exercise: 40%

Homework submission for each laboratory exercise, which is the 20% of the final lab grade


  • J. N. Ellinas, "Digital Image and Video Processing", Athens, 2010
  • R. C. Gonzalez, R. E. Woods, S. L. Eddins, "Digital Image Processing using MATLAB", Prentice Hall, 2004
  • R. C. Gonzalez, R. E. Woods, "Digital Image Processing", Prentice Hall, 2002
  • A. Κ. Jain, "Fundamentals of Digital Image Processing", Prentice Hall, 1989