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compressed_sensing_astronomy's Introduction

Compressed_sensing_astronomy

Authors : Hugo Caselles-Dupré & Philippe Peroumal

Disclaimer : several syntax errors can exist in the code. Use it wisely.

Compressed sensing applied to Astronomy

In this directory you can find the Notebook associated to my ENSAE ParisTech Project for the Compressed Sensing course, which was done with Philippe Peroumal.

We used Python 2.7.

In models.py, one can find the 3 algorithms we implemented in this project which are Hard and Soft-thresholding and Multiresolution mask denoising algorithm, and the implementation of the starlet transform.

In order to reproduce the results of the Notebook, the data (ngc2997.fits and AstroImages.fits) are provided in this repository.

If you have any questions : [email protected].

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