Image Processing and Analysis

Course Code: 
Spring Semester
Credit Points: 

Course outline

A. Lectures

During the course, the following material, among others, will be covered:

  • Introductory concepts for Image Processing & Analysis and their applications
  • Basic elements of 2-D signal processing and image transforms
  • Image acquisition systems and different types of degradation
  • Image enhancement methods
  • Image restoration methods
  • Techniques for lossless and lossy image compression
  • Reconstruction of 3D objects based on 2D projections
  • Edge detection and linking
  • Image segmentation
  • Shape description and representation
  • Object recognition
  • Basic structure of an image analysis system
  • Elements of color theory and color image processing basics.


B. Laboratory exercises and project



  • Exercise 1: Image transforms and image filtering in the frequency domain
  • Exercise 2: Image quantization (scalar and vector)
  • Exercise 3: Image compression using DCT trnasform
  • Exercise 4: Histogram based image processing
  • Exercise 5: Image restoration (inverse filering, Wiener filtering)
  • Exercise 6: Edge detection.



  • Each student will choose to implement one from a list of possible projects.

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