A global energy approach to facet model and its minimization using weighted least-squares algorithm

Abstract

A global energy approach and a weighted least-squares facet algorithm have been developed using the facet model. The global energy method gives a near-optimal estimation of the ideal image as predicted by the facet model using a regularization framework. The weighted least-squares facet algorithm improves the estimation of the facet parameters by taking into account the variances of estimations from different resolution cells. Experimental results show the validity of the global energy approach and the superiority of the WLS facet algorithms in both synthetic images and real range images.