Complex process of image color correction: a test of a target-based framework.

Abstract

This paper aims at presenting the complexity of the process of image target-based color correction (CC). We present issues encountered from acquisition to rendering using colorimetric traditional tools. Target-based CC can be seen as an optimization problem. We have tested SAT and HUE adaptive fine tuning (SHAFT) an automated framework for target-based CC. A key element of SHAFT is an iterative CIEDE2000 variation comparison between a reference and target image. In this work we replace the standard CIEDE2000 with the Euclidean color-difference formula for small-medium color differences in log-compressed Optical Society of America's Committee on Uniform Color Scales (OSA-UCS) space. Results are presented using both formulae. A discussion on the complexity of scene color departures and correction performances concludes the paper. The effect of real scene complexity is shown and how colors are subject to disordered shifts in the color space. Because of this complexity, the role of the CC method as a different color error minimizer emerges.