In this paper, we present a novel concept of color correction for consumer digital still camera (DSC) images. This concept is based on a hierarchical Bayesian image content analysis consisting of feature extraction and unsupervised clustering and on a set of color correction algorithms that have been optimized on the obtained characteristic image classes. Since the concept uses Bayesian inference to combine several color correction results, further available information (e.g., obtained from camera metadata) can be easily integrated into the color correction process.
Michael Schröder, Stefan Moser, "Automatic Color Correction based on Generic Content Based Image Analysis" in Proc. IS&T 9th Color and Imaging Conf., 2001, pp 41 - 45, https://doi.org/10.2352/CIC.2001.9.1.art00008