Wavelet Toolbox
Description
Analyzing Signals and Images
The Wavelet Toolbox graphical user interface (GUI) provides a comprehensive set of tools for analyzing 1-D and 2-D signals, including tools for wavelet analysis, wavelet packet analysis, denoising, and compression. For 1-D signals, you can use the GUI tools to:
- Perform discrete wavelet analysis of signals
- Perform continuous wavelet analysis of real signals using complex wavelets
- Denoise signals
- Estimate wavelet-based density
- Perform wavelet reconstruction schemes based on various wavelet coefficient selection strategies
- Randomly generate fractional Brownian motion
- Perform 1-D signal extension and truncation using periodic, symmetric, smooth, and zeropadding methods
- Perform 1-D signal clustering and classification using wavelet analyses (with Statistics Toolbox, available separately)
For 2-D signals, you can use the GUI tools to:
- Perform discrete wavelet analysis of images
- Fuse two images
- Perform translation-invariant denoising of images, using the stationary wavelet transform
- Reconstruct wavelet schemes based on various wavelet coefficient selection strategies
Wavelet denoising, with instant visualization of the results. Threshold settings can be applied using the denoising and compression tools in the Wavelet Toolbox graphical user interface (GUI).
