顾及拓扑与尖角的分类矢量数据分组压缩算法

A grouping compress algorithm of considering the topology andacute angle of classified vector data

针对现有拆分重组法对存在复杂内环以及复杂相交岛屿多边形的分类矢量数据的压缩结果中包含裂缝、重叠及大量尖锐夹角的问题,提出了一种顾及拓扑一致性与尖角的分组压缩方法。依据分类矢量数据中多边形与多边形及其内环的相交关系对矢量矢量数据分组,以修正后拆分重组法结合直接分割法和间接分割法对分类矢量数据分组压缩,压缩结果中不存在裂缝与重叠现象,维护了分类矢量数据的拓扑一致性;通过取回尖角点前后被删除的点,解决了压缩结果中尖角过多的问题。以Landsat8遥感影像分类矢量数据实验验证了文章算法,并与直接分割法、间接分割法、拆分重组法进行了对比分析,验证了本文方法的有效性。

Aiming at the problem of the compress result of the existing split recombination method to the classified vector data which existing complex inner ring and intersection between island polygons still contain crevice, overlapping and too many acute angles, a grouping compress algorithm of considering the topology and acute angle of classified vector data is proposed. Based on the intersecting relation of polygon and polygon, and inner ring, the classified vector data is grouped and compressed with combining revising split recombination method, direct segmentation method and indirect segmentation method by group, the compress result do not exist crevice and overlapping, and maintains the topological consistency of classi- fied vector data; besides, by retrieving the deleted points which are at the front and the behind of the ver- tex of acute angle, the problem of that there are too many acute angles in compressed result is solved. The paper conducts an experiment with the classified vector data of Landsat8 remote-sensing image, verifies the compression of classified vector data of taking the topology and acute angle into account, compares with direct segmentation method, indirect segmentation method and split recombination method, demon- strates the effectiveness of this method.