From Retinex to Automatic Color Equalization : issues in developing a new algorithm for unsupervised color equalization

In this work we present a comparison between two color equalization algorithms: Retinex, the famous model due to Land and McCann and ACE, a new algorithm, recently presented by the authors. These two algorithms share a common approach to color equalization but different computational models. The paper introduces the two models focusing on differences and common points. An analysis of their computational characteristics illustrates the way Retinex approach has influenced ACE structure and which aspects of the first algorithm have been modified in the second one and how. Their interesting equalization properties, like lightness and color constancy, image dynamic stretching, global and local filtering, data driven dequantization are qualitatively and quantitatively presented and compared, together with their ability to mimic the human visual system.