Wavelet Image Compression

William A. Pearlman is currently Professor Emeritus in the Electrical, Computer and Systems Engineering at Rensselaer Polytechnic Institute (RPI). He obtained B.S. and M.S. degrees from MIT in 1963 and his Ph.D. degree from Stanford University in 1974. He joined RPI in 1979 and became Professor in 1988. Prior to joining RPI, he had been a faculty member at the University of Wisconsin-Madison for five years. In addition, he had held industrial positions at Lockheed Missiles and Space Company and GTE-Sylvania and has consulted for several organizations. He has authored or co-authored more than 200 publications in the fields of signal, image and video compression, information theory, communications theory, and digital signal processing. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and of SPIE The International Society for Optical Engineering. At Visual Communications and Image Processing (VCIP) 2010 in Huangshan, China, where he was keynote speaker, he was presented a Certificate of Appreciation in recognition of his leadership and contributions to this conference since its inception in 1986. He received the IEEE Circuits and Systems Society 1998 Video Technology Transactions Best Paper Award and the IEEE Signal Processing Society 1998 Best Paper Award in the Area of Multidimensional Signal and Image Processing. He is co-inventor of two celebrated image compression algorithms, Set Partitioning in Hierarchical Trees (SPIHT) and Set Partitioning Embedded Block (SPECK) coding. In 2001, he received the Robert Bosch Foundation Award in Appreciation of Outstanding Works in the Field of Picture Coding. He has also delivered several keynote or invited plenary lectures on topics in signal compression and is lead author of the recent textbook, Digital Signal Compression: Principles and Practice, with co-author Amir Said, published by Cambridge University Press. He is also founder, president, and chief scientific officer of PrimaComp, Inc., a company that specializes in developing innovative software for signal and image compression.

• Introduction.- Characteristics of the Wavelet Transform.- Generic Wavelet-based Coding Systems.- The FBI Fingerprint Image Compression Standard.- Set Partition Embedded Block (SPECK) Coding.- Tree-based Wavelet Transform Coding Systems.- Rate Control for Embedded Block Coders.- Conclusion.