Shape from Shading by Estimating the Local Highest Points of Surface
基于表面局部最高点估计的明暗恢复形状算法

Imposing data-closeness as a hard constraint to needle-map of surface is proved to be a successful approach of shape from shading(SFS)technique in recent years, but the initialization needle map of the algorithm is much different from the true one of surface when the light source direction is not vertical and the uniqueness of needle map cannot be ensured.Aiming at avoiding the drawbacks of the algorithm based on the hard constraint, a modified method is presented in this paper.After the relationship of image gradient map and surface needle map is analyzed, the positions of the local brightest points of image are firstly detected and the positions of the local highest points of surface are estimated according to the irradiance equation.Secondly, at each point, the gradient direction of image is updated and the equation group is set up.For different cases of the equations, corresponding solutions are presented in this algorithm.The modified algorithm is effective when the illuminant direction is either vertical or non-vertical and the applicability of the algorithm is improved. Experimental results on synthetic and real images show that much accurate initial needle map and height are obtained.