colour_transfer

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colour_transfer

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Python implementation of the Iterative Distribution Transfer algorithm, by Pitie, F. et al.

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# colour_transfer

This module contains a Python implementation of the Iterative Distribution Transfer (IDT) algorithm, as described in

```
[Pitie05a] N-Dimensional Probability Density Function Transfer and its
Application to Colour Transfer. F. Pitie , A. Kokaram and R. Dahyot
(2005) In International Conference on Computer Vision (ICCV'05). Beijing,
October.

[Pitie05b] Towards Automated Colour Grading. F. Pitié , A. Kokaram and
R. Dahyot (2005) In 2nd IEE European Conference on Visual Media
Production (CVMP'05). London, November.

[Pitie07a] Automated colour grading using colour distribution transfer.
F. Pitie , A. Kokaram and R. Dahyot (2007) Computer Vision and Image
Understanding.

[Pitie07b] The linear Monge-Kantorovitch linear colour mapping for
example-based colour transfer. F. Pitié and A. Kokaram (2007) In 4th
IEE European Conference on Visual Media Production (CVMP'07). London,
November.

[Pitie08] Enhancement of Digital Photographs Using Color Transfer Techniques.
F. Pitié, A. Kokaram and R. Dahyot (2008). Single-Sensor Imaging. Sep 2008,
295 -321
```

The code is a port from the original in MatLab (https://github.com/frcs/colour-transfer).
Pictures used in the examples are taken from the original project at (https://github.com/frcs/colour-transfer) and were released free of copyrigths. 
Please, cite their publications when using this code and pictures.

This module contains also a Python implementation of the Linear Monge-Kantorovitch color rotation transformation.

The idea behind this implementation is to apply the colour mapping techniques to the transformation of galaxy colors in simulated catalogs to better reproduce the observed distributions.

Feel free to contact me at (tallada@pic.es) if you want more information.

colour_transfer

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