code CC743
credit_hours 3
title Data Compression and Image Processing
arbic title
credit hours 3
Description/Outcomes Modern technologies require processing of larger and larger amount of data while on the other hand smaller and smaller devices appear. These two contradictory requirements lead to increasing importance of data compression. Also, visual information plays an important role in almost all areas of our life. Today, much of this information is represented and processed digitally. Digital image processing is ubiquitous, with applications ranging from television to tomography, from photography to printing, from robotics to remote sensing. The course presents principles of data compression. The basic data compression methods are presented followed by most popular and frequently used compression algorithms. It also introduces thernfundamentals of digital image processing.rn
arabic Description/Outcomes
objectives Students will learn properties of various data compression methods which is very important when designing new information and communication systems.
  • Students will learn general principles of image processing.
  • To study applications in information systems, digital telephony, digital television, and multimedia Internet.
  • arabic objectives
    ref. books K. Sayood, Introduction to Data Compression (2nd edition), Morgan Kaufmann, 2000.
  • Fundamentals of Digital Image Processing, Anil K. Jain.
  • Digital Image Processing (2nd Edition), Rafael C. Gonzalez and Richard E. Woods
  • Ze-Nian Li and Mark S. Drew : Fundamentals of Multimedia,(Prentice Hall, 2004, ISBN: 0130618721)
  • Gibson, Berger, Lookabaugh, Lindbergh and Baker, Digital Compression for Multimedia, Principles and Standards, Morgan Kaufmann, 1998. (optional)
  • arabic ref. books
    arabic textbook
    objective set
    content set
    Course Content
    content serial Description
    1 Introduction on digital image processing
    2 Image acquisition and display, properties of the human visual system
    3 Color image representations, Sampling and quantization
    4 Linear/ nonlinear image filtering and correlation
    5 Some transforms and sub-band decompositions
    6 Contrast and color enhancement
    7 Dithering, image restoration
    8 Image registration
    9 Applications on Simple feature extraction and recognition techniques
    10 Introduction on data compression
    11 What is data compression?
    12 Basic methods, coding of integers, Elias codes, Fibonacci codes
    13 Entropy, 0th-order (empirical) entropy, kth-order (empirical) entropy
    14 Statistical methods, Shannon coding, Huffman coding, Adaptive Huffman coding
    15 Arithmetic coding and adaptive arithmetic coding
    16 JPEG Compression
    17 Advances in Data Compression