As explained in the introduction section of the page:
This toolbox implements several algorithms to compute sparse expansion in redundant dictionaries and to solve inverse problems with sparse regularization (and also TV regularization).
The content of the toolbox include:
- Overview
- Compressed sensing of exactely sparse signals with Fourier measurements.
- Compressed sensing of noisy approximately sparse signals with Gaussian measurements.
- Tomography inversion of an image with TV regularization.
- Sparse spikes deconvolution with L1 regularization and Matching Pursuit
- Image inpainting with sparse wavelets regularization
The page is a step by step description of examples that are very much noteworthy. The toolbox itself can be downloaded from Matlab Central. I have listed it in the reconstruction section of the Big Picture.
I am also noting the Gabriel has produced a toolbox for the Multiwavelet Alpert Transform. This is very nice. Other Toolboxes Gabriel has made can be found here.
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