ABSTRACT
In this chapter we describe a large collection of wavelet transforms discovered by Ingrid Daubechies. The Daubechies wavelet transforms are defined in the same way as the Haar wavelet transform-by computing running averages and differences via scalar products with scaling signals and wavelets. For the Daubechies wavelet transforms, the scaling signals and wavelets have slightly longer supports, i.e., they produce averages and differences using just a few more values from the signal. This slight change, however, provides a tremendous improvement in the capabilities of these new transforms, providing us with a set of powerful tools for signal processing.
