Morning Tutorial 4

• Abstract: This half-day tutorial on text, waveform and image compression is designed to teach
  1. up-to-date coding and compression procedures,
  2. the application of these procedures to different types of data and signals,
  3. widely-used compression formats and standards, and
  4. enough basic theory to enable the student to modify and improve standard procedures in specific applications, and to develop new techniques.

  It is targeted at people who want to learn about how compression works and how it is applied, as well as those who wish to become proficient in inventing and applying coding and compression techniques.
  
  

• Outline:
  
  
  • Basic coding and compression principles:
  • Entropy, decorrelation, etc.
  • Lossless and lossy compression.
  • Statistical properties of data files and compressibility limits.
  • Coding and compression techniques: Run-length coding Predictive coding Transform coding Huffman coding Lempel-Ziv-Welsh coding Codebook techniques Arithmetic coding
  • Compression of waveform data: music, speech, telemetry, etc.
  • Amplitude and spectral distributions and their effect on compressibility.
  • Stationarity and its effect on compressibility.
  • Linear and nonlinear predictive coding: theory and examples.
  • Predictive and arithmetic coding in lossless waveform compression.
  • Lossy waveform compression: measures of quality.
  • Lossy predictive coding of speech, music, and other waveforms.
  • Transform and subband coding methods and examples.
  • WAV, AU, and other standard compression formats for PC's and the web.
  • Compression of image and video data: photographic, radar, TV, etc.
  • Formats: black and white, gray scale, color
  • Two-dimensional discrete transforms.
  • Lossless image compression: bitmap and vector coding.
  • Lossy image compression: quantization, differencing, DCT, lossy transform methods.
  • The JPEG and MPEG compression standards.
  • Compression software provided with course.

• Speaker's Biographies:
  
  
  • Samuel D. Stearns has been a Distinguished Member of the Technical Staff at Sandia National Laboratories, Albuquerque, New Mexico, and is now a consultant. His principal technical areas are digital signal processing and adaptive signal processing. His most recent work has been in satellite telemetry and lossless waveform and image compression. Dr. Stearns has taught and advised dissertation research at several universities throughout the U.S., including the Universities of Central Florida, Colorado, and New Mexico, as well as Kansas State and Stanford Universities. He is a Fellow of the IEEE. His Fellow citation reads, "For contributions to education in digital and adaptive signal processing systems and algorithms." He has served in various IEEE activities and has published a number of papers in signal processing, adaptive signal processing, and related areas. He is a coauthor of the following Prentice-Hall texts: Signal Processing Algorithms in MATLAB (1996), Signal Processing Algorithms in Fortran and C (1993), Digital Signal Analysis, 2nd Ed. (1990), Signal Processing Algorithms (1987), Adaptive Signal Processing (1985).
    
    
  • Neeraj Magotra was born in Jamshedpur, India on December 5 1958. He obtained his B. Tech. in Electrical Engineering from the Indian Institute of Technology (Bombay, India) in 1980, his M.S. in Electrical Engineering from Kansas State University in 1982 and his Ph.D. in Electrical Engineering from the University of New Mexico in 1986. From 1987 until 1990 he held a joint appointment with Sandia National Laboratories and the department of Electrical and Computer Engineering (EECE) at the University of New Mexico, Albuquerque, New Mexico. He is currently employed as an Associate Professor in the EECE Department at the University of New Mexico. He has been involved in signal/image processing research in seismic, speech, biomedical and radar (synthetic array radar imaging) signal processing for the past fifteen years. Research areas include the theoretical design of algorithms (detection, enhancement, automatic target recognition and data compression - lossless as well as lossy) as well as real time implementation on DSP chips. Funding for this research has totaled $1.8M. Dr. Magotra has served as associate editor of the IEEE transactions on Signal Processing and on the organizing committee of ICASSP-90. He has also helped organize special sessions for the IEEE Asilomar Conference on Signals, Systems and Computers, the Midwest Symposium on Circuits and Systems, and the International Symposium on Circuits and systems. He is a member of Sigma Xi, Phi Kappa Phi, Tau Beta Pi, the Institute of Electrical and Electronics Engineers (IEEE) and the Seismological Society of America. He has authored and co-authored over eighty technical articles including journal papers, conference papers and technical reports, and also has taught short courses in the areas of general DSP, speech and radar DSP and real time DSP.
  
  

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Last Update:  February 4, 1999         Ingo Höntsch