This course is intended to give the necessary mathematical background on wavelets, and explore the main applications, both current and potential, to computer graphics.

An Introduction to Wavelet Analysis provides an overview of multiresolution analysis, wavelet series and wavelet estimators in the classical setting.

The aim of this book is to present, to a broad audience, mathematical tools and algorithms for signal representation.

Contents: Motivation through signal processing, analysis and synthesis; Vector Spaces with Inner Product; Fourier Series; The Fourier Transform; Discrete Fourier Transform; Linear Filters; Multiresolution Analysis; Wavelet Theory; Applications of Wavelets.

This book presents a succinct compendium of some of the more recent variants of DWTs.

A central goal of signal processing is to describe real life signals, be it for computation, compression, or understanding. This book presents a unified view of wavelets

Topics: Progressive-Regressive Strategy for Biometrical Authentication; Resolution Enhancement Based Image Compression Technique; Adaptive Wavelet Packet Transform; Scaling Factor Threshold Estimator in Different Color Models; Wavelet-Based Analysis of MCSA for Fault Detection in Electrical Machine; etc.