Based on the intuitive concept of time-frequency representations, this chapter provides high-level insights into why wavelets are good for image coding. After introducing the salient aspects of the compression problem and the transform coding problem, it highlights the key differences between the early class of sub-band coders and the more advanced class of modern-day wavelet image coders. Selecting the embedded zero tree wavelet coding structure embodied in the celebrated SPIHT algorithm as a representative of this latter class, its operation has been described by using a simple illustrative example. This chapter also discusses the role of wavelet packets as a simple but powerful generalization of the wavelet decomposition to offer a more robust and adaptive transform image-coding framework. The chapter then moves on to discuss the JPEG2000, which is a result of the rapid progress made in wavelet image coding research in the 1990s. The triumph of wavelet transform in the evolution of the JPEG2000 standard underlines the importance of the fundamental insights provided in this chapter into why wavelets are so attractive for image compression. 2005 Elsevier Inc. All rights reserved.
