Beyond White: Ground Truth Colors for Color Constancy Correction

Abstract:

A limitation in color constancy research is the inability to establish ground truth colors for evaluating corrected images. Many existing datasets contain images of scenes with a color chart included; however, only the chart's neutral colors (grayscale patches) are used to provide the ground truth for illumination estimation and correction. This is because the corrected neutral colors are known to lie along the achromatic line in the camera’s color space (i.e. R=G=B); the correct RGB values of the other color patches are not known. As a result, most methods estimate a 3×3 diagonal matrix that ensures only the neutral colors are correct. In this paper, we describe how to overcome this limitation. Specifically, we show that under certain illuminations, a diagonal 3×3 matrix is capable of correcting not only neutral colors, but all the colors in a scene. This finding allows us to find the ground truth RGB values for the color chart in the camera’s color space. We show how to use this information to correct all the images in existing datasets to have correct colors. Working from these new color corrected datasets, we describe how to modify existing color constancy algorithms to perform better image correction.

Diagonal Correction V.S. Full Matrix Correction

(A) input image before illumination correction. (B) corrected image using a conventional diagonal 3×3 matrix (i.e. white-balancing). (C) corrected image using a full 3×3 matrix estimated from the ground truth colors obtained by our approach. The reproduction angular errors for each 24 color patches are shown below each image as a heat map (red=high error, blue=low error).

Publication:

Beyond White: Ground Truth Colors for Color Constancy Correction (PDF), ICCV, 2015.

New Laboratory Image Sets:

Repurposing Existing Data Sets:

Acknowledgements:

This work was supported by an Adobe gift award.