Image intensity correction under illumination changes based on mixture Gaussian model

Abstract

Illumination changes in video sequences result in a drastic increase in the number of falsely detected change regions and make change detection unreliable. In this paper, we propose a novel approach for intensity correction under illumination variation. A mixture Gaussian model consisting of two density components associating with two classes is used. Based on Expectation- maximization algorithm, the statistical parameter estimations are performed. Under the assumption of Gaussian distribution for stationary pixels, the global intensity factor can be calculated for image intensity correction. Finally, two experiments are carried out to verify the proposed method. © 2013 Springer-Verlag.