A new algorithm for unsupervised global and local color correction

Abstract

In this work we present a new algorithm for digital images unsupervised enhancement with simultaneous global and local effects, called ACE for Automatic Color Equalization. It is based on a computational model of the human visual system that merges the two basic Gray World and White Patch global equalization mechanisms. Inspired by some adaptation mechanisms of the human vision, it realizes a local filtering effect by taking into account the color spatial distribution in the image. Like the human visual system, ACE is able to adapt to widely varying lighting conditions and to extract visual information from the environment efficaciously. It has shown promising results in achieving different equalization tasks, e.g. performing color and lightness constancy, realizing image dynamic data driven stretching, controlling the contrast. Characteristics, tests and results are presented.