Faculty of Engineering - Ain Shams University, Home

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Digital Video Engineering

What Will Learn?

  • Course Aims
    By the end of the course the students will be able to The basic theory and algorithms that are widely used in video compression. Current technologies and issues those are specific to video engineering. Developing hands on experience in using computers to process videos. Developing critical thinking about shortcomings of the state of the art in video compression.
  • Course Goals
  • Decent Work and Economic Growth
  • Industry, Innovation and Infrastructure
  • Sustainable Cities and Communities

Requirements

CSE381

Description

  • English Description

    Introduction to multimedia. Image data representation. Color in image and video. Basics of digital audio. The creation of digital music and audio. Encoding and compression, Segmentation, Recognition and interpretation, 3D imagery. Speech coders: Speech signal analysis, Waveform coders, Voice coders, Hybrid coders. Voice over IP, Video over IP. Lossless compression algorithms. Lossy compression algorithms. JPEG, JPEG2000. Video compression techniques: MPEG-1, MPEG-2, MPEG-4, MPEG-7, H.261, H.263, H.264, H.265 High Efficiency Video Coding (HEVC). Audio compression techniques, Vocoders. MPEG audio compression. Quality of Service (QoS). Applications.
  • Arabic Description

    Introduction to multimedia. Image data representation. Color in image and video. Basics of digital audio. The creation of digital music and audio. Encoding and compression, Segmentation, Recognition and interpretation, 3D imagery. Speech coders: Speech signal analysis, Waveform coders, Voice coders, Hybrid coders. Voice over IP, Video over IP. Lossless compression algorithms. Lossy compression algorithms. JPEG, JPEG2000. Video compression techniques: MPEG-1, MPEG-2, MPEG-4, MPEG-7, H.261, H.263, H.264, H.265 High Efficiency Video Coding (HEVC). Audio compression techniques, Vocoders. MPEG audio compression. Quality of Service (QoS). Applications.
  • Department
    Computer and Systems Engineering
  • Credit Hours
    3
  • Grades
    Total ( 100 ) = Midterm (25) + tr.Major Assessment (30 = tr.Industry 0% , tr.Project 15% , tr.Self_learning 5% , tr.Seminar 15% ) + tr.Minor Assessment (5) + Exam Grade (40)
  • Hours
    Lecture Hours: 2, Tutorial Hours: 2, Lab Hours: 0
  • Required SWL
    125
  • Equivalent ECTS
    5
  • Avinash Ramachandran, Decode to Encode: Master Complex Concepts Faster, Bridge Gaps and Be the Expert in Video Coding, 2018 - Fischer Walter. 2020. Digital Video and Audio Broadcasting Technology : A Practical Engineering Guide (version 4th ed). 4th ed. Cham: Springer.