【摘要】 提出了一种新的曲面三角网格模型参数化算法——加权最小二乘离散参数化方法 ( WLSDP)。该算法通过将空间数据点映射到平面凸区域 ,实现曲面三角模型参数化。它是离散保角映射 ( DCM)与离散保积映射( DAM)的线性组合 ,兼有二者的优点 ,如鲁棒性与低变形。用户通过调整该算法中的比例因子 q,可以得到满足不同特定问题要求的参数化结果更多还原

【Abstract】 A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of the discrete Conformal mapping(DCM) and the discrete Authalic mapping(DAM). It provides the good properties of both DCM and DAM, such as robustness and low distortion. By adjusting the scaling factor q embedded in the WLSDP, satisfactory parameterizations in different special applications can be achieved.更多还原