Face Image Relighting Using Locally Constrained Global Optimization

A face image relighting method using locally constrained global optimization is presented in this paper. Based on the empirical fact that common radiance environments are locally homogeneous, we propose to use an optimization based solution in which local linear adjustments are performed on overlapping windows throughout the input image. As such, local textures and global smoothness of the input image can be preserved simultaneously when applying the illumination transformation. Experimental results demonstrate the effectiveness of the proposed method comparing to some previous approaches.