Part-Time Programs in Engineering and Applied Science, Johns Hopkins University
Image Compression and Packet Video
525.759

Course Description
This course provides an introduction to the basic concepts and techniques used for the compression of digital images and video. Topics include two dimensional sampling and quantization; and coding techniques such as differential pulse code modulation, transform coding, subband/wavelet coding, and vector quantization. Motion compensation video coding and entropy coding techniques are covered, as well as coding standards such as JPEG and MPEG.  MPEG1, MPEG2 and MPEG 4 Video Compression algorithms will be covered.

This course is offered  in the fall semester.

Syllabus

  1. Introduction to Image Coding
  2. Two Dimensional Sampling and Convolution, Data Characteristics and Quantization
  3. Entropy and Entropy Encoders
  4. Predictive Coders, DPCM, Delta Modulation
  5. Transform Coders (DCT Based)
  6. Hybrid Coders, Predictive Transform Coders
  7. In Class Lab (Matlab Based) - Help with Labs
  8. Subband Based Coders, Wavelet Based Coders
  9. Vector Quantizers (VQ)
  10. Introduction to Video Coding (Motion Estimation)
  11. Motion Compensated Transform Coding - Video Compression Standards
  12. In Class Lab - Help with Labs
  13. MPEG-4 Elements
  14. In Class Lab (Demo of Finished Labs)
The homework assignments for this semester will consist of Matlab oriented projects focusing on different component technologies used in data compression. The University has purchased Matlab 5.2 for the computer lab (PC/Windows), and in addition, Mathworks, Inc. has granted permission for the students to obtain loaner copies of the software after the student has signed the Classroom Teaching Software License Agreement. The eight projects will cover: image display and measures, image quality assessment, numerical quantization, DPCM coding, JPEG style compression, sub-band coding and wavelets (using the UVIWAVE Toolbox), vector quantization, and motion estimation. Each lab will include an extra credit option. Final grades will depend on the number of labs completed and the number of extra credit options completed.

Prerequisites
525.427 Digital Signal Processing

Instructor
Nicholas Beser is on the staff of the Johns Hopkins University Applied Physics Laboratory, in the Stike Warfare Group of the Power Projections Systems Department. He has over 15 years experience in the area of data compression and is technical lead on several ongoing Navy projects incorporating image compression into tactical communication systems. Dr. Beser is also on several data compression standards committees including the National Imagery Transmission Format Standards and is a liaison to the ISO MPEG committee.

Course Section, Location, and Time
Please refer to the Course Schedule for section information, including time and location.

Computer Lab Requirements
PC Based Matlab (software will be supplied)

Textbook
Techniques & Standards for Image Video & Audio Coding by K. R. Rao and J. J. Hwang
Recommended Text: Mastering Matlab 5 by Duane Hanselman and Bruce Littlefield
 

Return to Part-Time Engineering
Return to Whiting School of Engineering
Return to JHUniverse
Electrical Engineering

updated September 1998