Robust Motion Estimation Using Chrominance Information in Color Image Sequences

This paper describes a method for incorporating the chromin-ance information when estimating motion in a colour image sequence. It is based on a Maximum-Likelihood (ML) formulation of the motion estimation problem which assumes homogeneous additive Gaussian noise in each colour component, with known inter-eld correlation statistics. It deenes a noise-decorrelating colour space transform which provides a simple implementation of the ML formulation. Results for noisy syn-thesised colour sequences with known motion and noise statistics demonstrate the superiority of the exact ML formulation over straightforward, unweighted three-component estimation, most noticeably in high noise conditions.