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Shearlet Grid
Lupe

Matlab Toolbox for Shearlets

ShearLab is a MATLAB library developed for processing two- and threedimensional data with a certain class of basis functions named shearlets. Such shearlet systems are particularly well adapted to represent anisotropic features (such as curves) that are often crucial in multidimensional data. The resulting representation has proven well-suited for image processing tasks such as inpainting, denoising or image separation. On this website we provide the full MATLAB code, a framework for numerical tests as well as general information on shearlets.

The ShearLab 3D Toolbox (Ver. 1.0) and older versions of ShearLab can be downloaded from http://www.shearlab.org. Further, you can find ShearLab3D on the webpage of  the Oberwolfach References on Mathematical Software here and on swMATH here.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

If you have questions or comments, please contact .

 

 

PROMP

PROMP, PRe-projected Orthogonal Matching Pursuit, is a modification of the OMP-algorithm for recovery of sparse integer-valued signals. The main idea is to use l2-minimization and thresholding to form a support approximation prior to warm starting OMP with this support approximation. More information can be found in the publication “PROMP: A Sparse Recovery Approach to Lattice Valued Signals”.

The software package, which is to be used with MATLAB, can be downloaded here (ZIP, 5,7 KB). It contains an implementation of PROMP, as well as various scripts which can be used to test its performance.

The package is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

Please address any comments and/or questions to .


 

 

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