An optimal mergence method in virtual endoscopy system

The computation of surface normal vector is an important task in the rendering stage of virtual endoscopy system. Usually, it is generated by two kinds of computational methods: distance gradient and density gradient. Based on the discovery that these two approaches are principally complementary to each other, in this paper, we proposed an optimal mergence algorithm to generate high-quality rendered images. To investigate the accuracy and efficiency of mergence, we designed and test two computational mergence methods respectively: algebraic mergence and geometrical mergence. The extensive experiment results show that our algorithm greatly improves the image quality than previous approaches, and the geometric mergence can integrate the advantages of the two gradient-based methods for computation of surface normal vector.