Storage-efficient reconstruction framework for planar contours
Storage-efficient reconstruction framework for planar contours
复制标题
平面轮廓的存储高效重建框架
DOI：
10.1080/10095020.2016.1194603
复制
发表时间：
2017
影响因子：
6
通讯作者：
Hiroyuki GOTO，Yoichi SHIMAKAWA
中科院分区：
文献类型：
--
作者：
Hirotsu N;Inoue K and Yamamoto K;Hiroyuki GOTO，Yoichi SHIMAKAWA
开发了一种用于制图平面轮廓的存储高效重建框架。使用较少数量的控制点，我们的目标是计算面积和周长以及重建平滑曲线。输入数据形成一个定向轮廓，其每个控制点由三个值组成：笛卡尔坐标（x，y）和切线角θ。开发了两种类型的插值方法，其中一种基于圆弧样条，另一种基于三次埃尔米特样条。基于圆弧样条的方法重建了G1连续曲线，可以计算出精确的面积和周长。使用基于 Hermite 样条的方法的好处是，它可以在大多数控制点上实现 G2 连续性，并且可以获得精确的面积，而得到的周长是近似的。在解析定义曲线的数值实验中，使用较少数量的控制点可以更准确地计算面积和周长。在另一个使用数字高程模型数据的实验中，重建的轮廓比传统方法更平滑。
A storage-efficient reconstruction framework for cartographic planar contours is developed. With a smaller number of control points, we aim to calculate the area and perimeter as well as to reconstruct a smooth curve. The input data forms an oriented contour, each control point of which consists of three values: the Cartesian coordinates (x,y) and tangent angleθ. Two types of interpolation methods are developed, one of which is based on an arc spline while the other one is on a cubic Hermite spline. The arc spline-based method reconstructs a G1continuous curve, with which the exact area and perimeter can be calculated. The benefit of using the Hermite spline-based method is that it can achieve G2continuity on most control points and can obtain the exact area, whereas the resulting perimeter is approximate. In a numerical experiment for analytically defined curves, more accurate computation of the area and perimeter was achieved with a smaller number of control points. In another experiment using a digital elevation model data, the reconstructed contours were smoother than those by a conventional method.