https://github.com/jolideco/jolideco

A Python package for Poisson joint likelihood deconvolution
https://github.com/jolideco/jolideco

deconvolution gamma-ray-astronomy image-analysis maximum-a-posteriori-estimation pytorch x-ray-astronomy

Last synced: about 2 hours ago
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A Python package for Poisson joint likelihood deconvolution

• Host: GitHub
• URL: https://github.com/jolideco/jolideco
• Owner: jolideco
• License: bsd-3-clause
• Created: 2022-05-18T02:12:51.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-29T21:48:22.000Z (28 days ago)
• Last Synced: 2024-09-13T18:53:25.834Z (13 days ago)
• Topics: deconvolution, gamma-ray-astronomy, image-analysis, maximum-a-posteriori-estimation, pytorch, x-ray-astronomy
• Language: Python
• Homepage:
• Size: 4.1 MB
• Stars: 3
• Watchers: 6
• Forks: 2
• Open Issues: 9
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

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README

        
.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat

    :target: http://www.astropy.org

    :alt: Powered by Astropy Badge

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    :alt: Documentation Status

    :scale: 100%

    :target: https://jolideco.readthedocs.io/en/latest/?badge=latest

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    :target: https://zenodo.org/doi/10.5281/zenodo.10870554

    :alt: DOI

Jolideco: a Python package for Poisson Joint Likelihood Deconvolution

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.. image:: https://raw.githubusercontent.com/jolideco/jolideco/main/docs/jolideco-illustration.png

    :width: 600

    :alt: Jolideco illustration

    :align: center

Jolideco is a Python package for Joint Likelihood Deconvolution of astronomical images affected by

Poisson noise. It allows you to deblur and denoise images and do a joint image reconstruction of

multiple images from different instruments, while taking their specific instrument response functions,

such as point spread functions, exposure and instrument specific background emission into account.

To ensure a high fidelity of reconstructed features in the images, Jolideco relies on a patch based

image prior, which is based on a Gaussian Mixture Model (GMM). 

Contributing Code, Documentation, or Feedback

---------------------------------------------

Jolideco is an open-source project and we welcome contributions of all kinds: 

new features, bug fixes, documentation improvements, and more. If you are interested

in contributing, please get in contact with the maintainers and make sure to read the

`Code of Conduct `_.

Citation

--------

When using Jolideco, please cite the `version you used from Zenodo `_ 

and the following paper reference:

.. code-block:: bibtex

    TBD

Further Resources

------------------

Please also take a look at the following associated repositories:

- `Jolideco GMM Library `_

- `Jolideco Fermi-LAT Example `_

- `Jolideco Chandra Example `_

- `Webpage with Result Comparisons for Toy Datasets `_

- `Jolideco Performance Benchmarks `_

Contributing

------------

While contributions are welcome in general, currently I cannot review PRs, nor help with implementations,

because of a lack of time. So PRs are unlikely to get merged. However any kind of bug report or feature

requests are welcome as well.