Compression

Wavelet spatial orientation tree, SPIHT, EZW, WDR, AWDR, matching pursuit

Compress signals and images using wavelet analysis and matching pursuit methods.

Functions

`wcompress`	True compression of images using wavelets
`wdencmp`	Denoising or compression
`wpdencmp`	Denoising or compression using wavelet packets
`measerr`	Quality metrics of signal or image approximation

`sensingDictionary`	Sensing dictionary for sparse signal recovery
`matchingPursuit`	Recover sparse signal using matching pursuit algorithm
`basisPursuit`	Recover sparse signal using the basis pursuit algorithm

Wavelet Data Compression
Learn how to obtain sparse representation of a signal using wavelets.
2-D Wavelet Compression
Use wavelet 2-D true compression to reduce the number of bits needed to represent an image.
2-D Wavelet Packet Analysis
Analyze an image with wavelet packets using the Wavelet Analyzer app.
Wavelet Compression for Images
Learn about quantization for true compression of images and about different compression methods.
Data Compression using 2-D Wavelet Analysis
The purpose of this example is to show how to compress an image using two-dimensional wavelet analysis.

Matching Pursuit
Create sensing dictionaries and perform matching pursuit on 1-D signals.
Matching Pursuit Algorithms
Learn about basic, orthogonal, and weak orthogonal matching pursuit algorithms.