Light Field toolbox - Recolouring step

This code is mostly meant to correct colour inconsistencies in Light Field datasets taken using plenoptic cameras [1]. This will allow you to propagate the colours from the centre of a Light Field to all the images, which will ensure you get consistent sub-aperture images accross the whole set.

If you use or adapt any part of this code in your work, please remember to cite the appropriate paper [1].

• Authors : Pierre Matysiak (matysiap@scss.tcd.ie), Mairéad Grogan (mgrogan@tcd.ie)
• Copyright : (c) 2018 V-Sense
• License : GPL v3+, see GPLv3.txt

For additional details and visual results, see our webpage.

The additional post-processing steps presented in [1] (RAW data demultiplexing and denoising) are not present in this repository. You can find them respectively here and here.

The proper order in which to use these tools is : RAW data demultiplexing --> Recolouring --> Denoising.

Usage

For simplicity's sake, we made it so that you only have to use the one file, everything else is done automatically :

• put any number of datasets in the folder called "data"
• at the beginning of the file "recolour_centre_neighbour.m", add/replace the paths to your datasets, assuming that the root folder is ".../data/"
• launch the code by calling "recolour_centre_neighbour.m" ; no arguments are necessary.

Please note that the recolouring code uses OpenMP, please make sure you have the proper dependancies installed and that your compiler supports it.

References

[1] P. Matysiak, M. Grogan, M. Le Pendu, M. Alain and A. Smolic, "A Pipeline for Lenslet Light Field Quality Enhancement", International Conference on Image Processing (ICIP) 2018.

[2] M. Grogan and R. Dahyot, “Robust registration of gaussian mixtures for colour transfer”, ArXiv e-prints (May 2017). arXiv:cs.CV/1705.06091.

[3] Y. Hu, R. Song, and Y. Li, “Efficient coarse-to-fine patchmatch for large displacement optical flow”, in Proc. CVPR, 2016.