虚拟内窥镜系统中表面法向量的计算

Computation of Surface Normal Vector in Virtual Endoscope System

表面法向量计算是虚拟内窥镜系统中的一个重要问题 ,通常采用距离梯度法和密度梯度法计算。作者对这两种方法的优缺点作了讨论 ,针对它们彼此具有互补的特点 ,提出将距离梯度图像和密度梯度图像相融合的方法 ,并分别设计了代数融合和几何融合两种方法。实验结果显示 ,融合后的图像质量有了明显改善 。

The computation of surface normal vector is an important task in the realization of Virtual Endoscope(VE) system.Normally, it is generated by two kinds of computational approaches: distance gradient or density gradient. Based on the discovery that these two approaches are principally complementary to each other. In this paper, the authors proposed a new algorithm to calculate the surface normal vector by merging the rendered images from distance gradient and density gradient approaches. To carry out the merging accurately and efficiently, two computational merging methods were designed respectively: algebraic merging and geometrical merging. The extensive experiment results show that the algorithm greatly improves the image quality and the geometrical merging performs superiorly to algebraic merging.