The Chromagenic color constancy algorithm estimates the light color given two images of the same scene, one filtered and one unfiltered. The key insight underpinning the chromagenic method is that the filtered and unfiltered images are linearly related and that this linear relationship correlates strongly with the illuminant color. In the original method the best linear relationship was found based on the assumption that the filtered and unfiltered images were registered. Generally, this is not the case and implies an expensive image registration step.
This paper makes three contributions. First, we use the Monge-Kantorovich (MK) method to find the best linear transform without the need for image registration. Second, we apply this method on chromagenic pairs of facial images (used for Kampo pathophysiology diagnosis). Lastly, we show that the MK method supports better color correction compared with solving for a 3 × 3 correction matrix using the least squares linear regression method when the images are not registered.
|Title of host publication||Computational Color Imaging|
|Subtitle of host publication||7th International Workshop, CCIW 2019, Chiba, Japan, March 27-29, 2019, Proceedings|
|Editors||Shoji Tominaga, Raimondo Schettini, Alain Trémeau, Takahiko Horiuchi|
|Publication status||Published - 20 Feb 2019|
|Name|| Lecture Notes in Computer Science |