We are strong supporters of reproducible research, following the statement above by David L. Donoho. Thus, all MATLAB-code related to our publications as well as additional MATLAB-code for simulations will be included here as it becomes available.

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If you use or mention this code in a publication, please cite this website as well as the following paper:
G. Kutyniok, W.-Q. Lim, R. Reisenhofer:
"ShearLab 3D: Faithful Digital Shearlet Transforms Based on Compactly Supported Shearlets".
ACM Trans. Math. Software 42 (2016), Article No.: 5.

• ShearLab3D v1.1 (current version)
• ShearLab3D Manual
• 2D Experiments (denoising, inpainting, separation)
• 3D Experiments (denoising, inpainting)
• Numerical Experiments from "ShearLab 3D: Faithful Digital Shearlet Transforms Based on Compactly Supported Shearlets"
• ShearLab3D v1.01 (older version)

• Full support and unified treatment of 2D and 3D data.
• Optimized for CUDA (requires MATLAB Parallel Processing Toolbox and CUDA capable NVidia graphics card)
• Shearlets are compactly supported in the time domain.
• Examples for applications like image and video denoising, inpainting and geometric separation problems.

 

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• pyShearLab is a Python toolbox that implements a 2D Shearlet transform based on ShearLab 3D.
• author: Stefan Look

• pyShearLab project website (further information and download)

 

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• Shearlab.jl provides an implementation of ShearLab 3D in Julia. Currently only 2D transforms are available but an extension to 3D is planned for the future.
• author: Hector Andrade Loarca

• Shearlab.jl (further information and download)
• Fwt.jl (wavelet package by the same author)

 

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• tfShearlab provides an implementation of ShearLab 3D in tensorflow. In this case images and coefficients are considered two-dimensional tensors. This implementation is the fastest so far due to the GPU functionalities in tensorflow and is ideal to use when doing the shearlet transform in a deep learning application.
• author: Hector Andrade Loarca

• tfShearlab (further information and download)

 

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• BendLab Toolbox
• Lessig, Petersen, Schäfer: Bendlets: A Second-Order Shearlet Transform with Bent Elements

• This library can be used stand-alone or as "add-on" to ShearLab. In the latter case, extract the archive in the root directory of ShearLab. The new files have the prefix BL. See BLcontents.m and the files BL*.m in the Examples folder for details.
• authors: Christian Lessig, Philipp Petersen, Martin Schäfer

 

ShearLab 1.1 (Implementation based on Cartesian Grids)

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• ShearLab-1.1 (32-bit Windows)
• ShearLab-1.1 (32-bit Mac/Linux)
• ShearLab-1.1 (64-bit, Windows/Mac), requires Wavelet Toolbox
• ShearLab-1.1 (64-bit, Linux), requires Wavelet Toolbox

• Digital shearlet transform in spatial domain based on compactly supported, separable shearlets.
• Morphological component analysis using wavelets and shearlets (image separation toolbox).
• (Shift invariant) Fourier based shearlet transform.

 

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• ShearLab-PPFT-1.0

• Digital shearlet transform based on pseudo-polar FFT.
• Framework for quantifying performance of parabolic scaling algorithms.