New Generation Signal and Image Analysis!

Discover the power of wavelets! Wavelet analysis, in contrast to Fourier analysis, uses approximating functions that are localized in both time and frequency space. It is this unique characteristic that makes wavelets particularly useful, for example, in approximating data with sharp discontinuities.

Engineers, physicists, astronomers, geologists, medical researchers, and others have already begun exploring the extraordinary array of potential applications of wavelet analysis, ranging from signal and image processing to data analysis. Wavelet Explorer introduces you to this exciting new area and delivers a broad spectrum of wavelet analysis tools to your desktop.

Wavelet Explorer's ready-to-use functions and utilities let you apply a variety of wavelet transforms to your projects. Generate commonly used filters such as the Daubechies' extremal phase and least asymmetric filters, coiflets, spline filters, and more. Visualize wavelets and wavelet packets and zoom in on their details. You can transform your data to a host of wavelet bases, wavelet packet bases, or local trigonometric bases and do inverse transforms in one and two dimensions. Then view the transform in time-frequency space, selecting different bases and boundary conditions. Data compression and denoising are surprisingly simple procedures with Wavelet Explorer's built-in functions.

In addition to its impressive collection of powerful analysis and visualization tools, Wavelet Explorer is an excellent interactive tutorial for those who are new to wavelet theory. Clear examples start with the basics about wavelets and how to explore wavelet properties, then demonstrate how you can use the system to apply wavelet analysis techniques in your field.

Written in the Mathematica language, Wavelet Explorer's built-in functions and utilities are all fully programmable. Take advantage of Mathematica's thousands of powerful computational and visualization algorithms as you extend and customize your own wavelet analysis tools.

Features

Orthogonal and Biorthogonal Filters

• Haar Filter
• Daubechies' Extremal Phase Filters
• Daubechies' Least Asymmetric Filters
• Coiflets
• Shannon Filter
• Meyer Filters
• Battle-Lemarie Filters
• Biorthogonal Spline Filters

Orthogonal and Biorthogonal Filters

• Scaling Function, Wavelets, and Wavelet Packets
• Generates Scaling Functions, Wavelets, and Wavelet Packets from a Given Filter
• Zooms In on the Details of Scaling Functions, Wavelets, and Wavelet Packets
• Computes the Derivatives of Scaling Functions and Wavelets

Wavelet and Wavelet Packet Transforms

• Multiresolution Decomposition
• One- and Two-Dimensional Wavelet Transforms Using Orthogonal and Biorthogonal Wavelets
• One- and Two-Dimensional Wavelet Packet Transforms Using
• Orthogonal Wavelet Packets

Local Trigonometric Transforms

• One-Dimensional Malvar Transforms
• One- and Two-Dimensional Sine and Cosine Transforms
• One- and Two-Dimensional Sine and Cosine Packet Transforms

Data Compression and Denoising

• One-Dimensional Signal Compression
• Two-Dimensional Image Compression
• Denoising of One- and Two-Dimensional Data