Digital Image Processing



Vision provides humans with extremely important information like no other of the human senses. This is clear in all aspects of human activities and in particular in those related to science. The recent advances of processing technology and optical sensors have enabled the establishment of image processing and computer vision among the prominent fiels of computer science. Digital image processing is used for two distinct purposes: (1) image enhancement, so as to facilitate interpretation by a human observer and (2) digital image analysis, so as to allow unsupervised recognition and interpretation of the image contents. The course aims to present the basic algorithms and methodologies for both purposes, both in the spatial and frequency domain.

Course Contents

  • Introduction to Digital Image Processing
  • 2-D Signals and Systems – Background Information
  • Sampling and Digitization Issues
  • Image Enhancement and Restoration
  • Binary Image Processing – Morphological Operators
  • Image Segmentation – Edge Detection
  • Image Transformations (Fourier, DCT, Hadamard, etc.)
  • Analysis in the frequency domain
  • Digital Image Compression
  • Digital Image Analysis – Computer Vision
  • Texture Analysis – Region of Interests
  • Other areas: eg Watermarking, Information Retrieval, etc.