Using the Random Sprays Retinex Algorithm for Global Illumination Estimation

Abstract

In this paper the use of Random Sprays Retinex (RSR) algorithm for global illumination estimation is proposed and its feasibility tested. Like other algorithms based on the Retinex model, RSR also provides local illumination estimation and brightness adjustment for each pixel and it is faster than other path-wise Retinex algorithms. As the assumption of the uniform illumination holds in many cases, it should be possible to use the mean of local illumination estimations of RSR as a global illumination estimation for images with (assumed) uniform illumination allowing also the accuracy to be easily measured. Therefore we propose a method for estimating global illumination estimation based on local RSR results. To our best knowledge this is the first time that RSR algorithm is used to obtain global illumination estimation. For our tests we use a publicly available color constancy image database for testing. The results are presented and discussed and it turns out that the proposed method outperforms many existing unsupervised color constancy algorithms.

Files

Full Paper as PDF

BibTeX Citation

Source Code

DOI

10.20532/ccvw.2013.0018

https://doi.org/10.20532/ccvw.2013.0018

BibTeX

@InProceedings{10.20532/ccvw.2013.0018,
  author =       {Nikola Bani{\' c} and Sven Lon{\v c}ari{\' c}},
  title =        {Using the Random Sprays Retinex Algorithm for Global
                  Illumination Estimation},
  booktitle =    {Proceedings of the Croatian Compter Vision Workshop,
                  Year 1},
  pages =        {3-8},
  year =         2013,
  editor =       {Lon{\v c}ari{\' c}, Sven and {\v S}egvi{\' c},
                  Sini{\v s}a},
  address =      {Zagreb},
  month =        {September},
  organization = {Center of Excellence for Computer Vision},
  publisher =    {University of Zagreb},
  abstract =     {In this paper the use of Random Sprays Retinex
                  algorithm for global illumination estimation is
                  proposed and its feasibility tested. The algorithms
                  based on the Retinex model provide local
                  illumination estimation for each pixel and they
                  often have a high computation cost while another
                  problem is the noise in the resulting images. As the
                  assumption of the uniform illumination holds in many
                  cases, it should be possible to use the mean of
                  local illumination estimation of Retinex algorithms
                  as a global illumination estimation because in that
                  case their performance can be easily measured and
                  there is also a possibility of a significantly lower
                  computation cost. Therefore we propose a method for
                  estimating global illumination estimation based on
                  local Retinex results. For our tests we use a
                  publicly available color constancy image data base
                  for testing. The results are presented and discussed
                  and it turns out that the proposed method
                  outperforms many existing unsupervised color
                  constancy algorithms.},
  doi =          {10.20532/ccvw.2013.0018},
  url =          {https://doi.org/10.20532/ccvw.2013.0018}
}