Data Compression

  • Computer Science |

Description

This course provides an overview of classical and modern techniques and algorithms of various types of data compression. It covers statistical and dictionary methods, lossless and lossy compres-sion algorithms in text, image, audio, and video compression.

Program

Bachelor of Computer Science - 144 CRs

Objectives

  • 1. Realize the need for data compression.
    2. Differentiate between lossless and lossy compression techniques.
    3. Understand three statistical lossless compression encoding techniques (Run-length, Huffman, Adaptive Huffman, and Arithmetic).
    4. Understand two dictionary lossless compression encoding techniques (LZ77, LZW)
    5. Understand the main idea behind JPEG standard for compression of still images.
    6. Understand the main idea behind MPEG standard for compression of video and its relation to JPEG
    7. Implement some of the mentioned compression encoding techniques using Python or Matlab.

Textbook

Khalid Sayood, Introduction to Data Compression, Morgan Kaufmann

Course Content

content serial Description
1Introduction to data compression, lossy and lossless techniques
2Information Content and Entropy
3Huffman Coding
4Adaptive Huffman Coding
5Arithmetic coding
6Dictionary Coding, LZW, LZ77
77th week exam
8Audio Compression 1
9Audio Compression 2
10Image Compression 1
11Image Compression 2
1212th week exam
13Video Compression 1
14Video Compression 2
15Revision
16Final exam

Markets and Career

  • Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
  • Electrical power feeding for civil and military marine and aviation utilities.
  • Electrical works in construction engineering.

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