1. Introduction; P.N. Topiwala. I: Preliminaries. 2. Preliminaries; P.N. Topiwala. 3.Time-Frequency Analysis, Wavelets and Filter Banks; P.N. Topiwala. 4. Introduction to Compression; P.N. Topiwala. 5. Symmetric Extension Transforms; C.M. Brislawn. II: Still Image Coding. 6. Wavelet Still Image Coding: A Baseline MSE and HVS Approach; P.N. Topiwala. 7. Image Coding Using Multiplier-Free Filter Banks; A. Docef, et al. 8. Embedded Image Coding Using Zerotrees of Wavelet Coefficients; J.M. Shapiro. 9. A New Fast/Efficient Image Codec Based on Set Partitioning in Hierarchical Trees; A. Said, W.A. Pearlman. 10. Space-Frequency Quantization for Wavelet Image Coding; Zixiang Xiong, et al. 11. Suband Coding of Images Using Classification and Trellis Coded Quantization; R. Joshi, T.R. Fisher. 12. Low-Complexity Compression of Run Length Coded Image Subbands; J.D. Villasenor, Jiangtao Wen. III: Special Topics in Still Image Coding. 13. Fractal Image Coding as Cross-Scale Wavelet Coefficient Prediction; G. Davis. 14. Region of Interest Compression in Subband Coding; P.N. Topiwala. 15. Wavelet-Based Embedded Multispectral Image Compression; P.N. Topiwala. 16. The FBI Fingerprint Image Compression Specification; C.M. Brislawn. 17. Embedded Image Coding Using Wavelet Difference Reduction; Jun Tian, R.O. Wells, Jr. 18. Block Transforms in Progressive Image Coding; Trac D. Tran, Truong Q. Nguyen. IV: Video Coding. 19. Brief on Video Coding Standards; P.N. Topiwala. 20. Interpolative Multiresolution Coding of Advanced TV with Subchannels; K.M. Uz, et al. 21. Subband Video Coding for Low to High Rate Applications; W.C. Chung, et al. 22. Very Low Bit Rate Video Coding Based on Matching Pursuits;R. Neff, A. Zakhor. 23. Object-Based Subband/Wavelet Video Compression; Soo-Chul Han, J.W. Woods. 24. Embedded Video Subband Coding with 3D SPIHT; W.A. Pearlman, et al. A: Wavelet Image and Video Compression &endash; The Homepage; P.N. Topiwala. B: The Authors. C: Index.

An exciting new development has taken place in the digital era that has captured the imagination and talent of researchers around the globe - wavelet image compression. This technology has deep roots in theories of vision, and promises performance improvements over all other compression methods, such as those based on Fourier transforms, vectors quantizers, fractals, neural nets, and many others. It is this revolutionary new technology that is presented in Wavelet Image and Video Compression, in a form that is accessible to the largest audience possible.
Wavelet Image and Video Compression is divided into four parts. Part I, Background Material, introduces the basic mathematical structures that underly image compression algorithms with the intention of providing an easy introduction to the mathematical concepts that are prerequisites for the remainder of the book. It explains such topics as change of bases, scalar and vector quantization, bit allocation and rate-distortion theory, entropy coding, the discrete-cosine transform, wavelet filters and other related topics. Part II, Still Image Coding, presents a spectrum of wavelet still image coding techniques. Part III, Special Topics in Still Image Coding, provides a variety of example coding schemes with a special flavor in either approach or application domain. Part IV, Video Coding, examines wavelet and pyramidal coding techniques for video data.
Wavelet Image and Video Compression serves as an excellent reference and may be used as a text for advanced courses covering the subject.