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Fast Multidimensional Signal Processing using Julia with Shearlab.jl

Description

Shearlab is a Julia Library with toolbox for two- and threedimensional data processing using the Shearlet system as basis functions which generates a sparse representation of cartoon-like functions with applications on Signal Processing, Compressed Sensing, 3D Imaging, MRI Imaging and a lot more, with visible improvements with respect of the Wavelet Transform in representing multidimensional data.

Abstract

The Shearlet Transform was proposed by the Professor Gitta Kutyniok (http://www.tu-berlin.de/?108957) and her colleagues as a multidimensional generalization of the Wavelet Transform, and since then it has been adopted by a lot of Companies and Institutes by its stable and optimal representation of multidimensional signals. Shearlab.jl is a already registered Julia package (https://github.com/arsenal9971/Shearlab.jl) based in the most used implementation of Shearlet Transform programmed in Matlab by the Research Group of Prof. Kutyniok (http://www.shearlab.org/software), it was developed as a project apart of my PhD studies but ended up being the main computational tool of them, used mainly to reconstruct the Light Field of a 3D Scene from Sparse Photographic Samples of Different Perspectives with Stereo Vision purposes.

Why I think this will be an interesting thing to present at JuliaCon 2017?

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