Illumination robust optical flow estimation by illumination-chromaticity decoupling

In this paper, a novel optical flow algorithm which is robust to illumination variation is proposed. HSL color space is adopted to decouple illumination and chromaticity information. The chromaticity component is normalized by chroma and transformed to the cartesian coordinate. Then, the decoupled distance is defined using both illumination and chromaticity. Cost function for the optical flow is formulated using l₁ norm of the decoupled distance with Huber norm regularization term. The cost function is efficiently minimized by utilizing Legendre-Fenchel transform. Optical flow field is further refined via weighted median filter whose weight is also based on the decoupled distance. Experimental results show that the proposed method works robustly even in the presence of severe illumination variation.