Software

Reproducible Research"An article about computational science in a scientific publication is not the scholarship itself, it is merely advertising of the scholarship. The actual scholarship is the complete software development environment and the complete set of instructions which generated the figures."

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.

ShearLab 3D


Citation

If you use or mention this code in a publication, please cite www.shearlab.org 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.

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Main Features

  • 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.

 

pyShearLab


Info

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

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Shearlab.jl (Julia)


Info

  • 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

Downloads

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

 

tfShearlab (Tensorflow)


Info

  • 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

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BendLab


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Info

  • 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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Main Features

  • 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.

 

ShearLab PPFT 1.0 (Implementation based on Pseudo-Polar Grids)


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Main Features

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