首页> 外文会议>第21届国际摄影测量与遥感大会(ISPRS 2008)论文集 >ROBUST EXTRACTION OF ANCIENT BURIAL MOUNDS IN BRUSHLAND FROM LASER SCANNING DATA
【24h】

ROBUST EXTRACTION OF ANCIENT BURIAL MOUNDS IN BRUSHLAND FROM LASER SCANNING DATA

机译:从激光扫描数据中可靠地提取布鲁塞尔古朴的山脉

获取原文

摘要

Moroyama town, where is located in the southwestern part of Saitama Prefecture is a historical town including more than 80 ancient burial mounds. These ancient burial mounds locate in brushland. The diameters of these ancient burial mounds are about 5-15m, but there are small mounds less than 5m diameter which shows only top part of the mounds, bigger mounds more than 20m diameter and keyhole-shaped mounds. Therefore, it is supposed that some of the small ancient burial mounds are not yet found because the ancient burial mounds are covered with trees. The authors have been concentrating on developing an efficient extraction method for ancient burial mounds which are covered with trees using laser scanning data. However, filtering method and threshold values for robust extraction of the mounds from smaller to bigger are issues. With this motive, filtering and thresholding approach for an efficient extraction from smaller to bigger mounds using pyramid filters are proposed in this paper. The most remarkable points of this approach are its ability to extract from smaller and bigger mounds efficiently. In particular, the proposed pyramid filtering show the ability to extract smaller mounds less than 5m diameter, and 11 mounds are newly extracted by the method. Furthermore, in order to perform visual investigation, landscape animation for the mound area is generated in this paper.
机译:Sa玉县西南部的Moroyama镇是一座历史悠久的城镇,拥有80多个古墓葬。这些古老的墓穴位于灌木丛中。这些古墓冢的直径约为5-15m,但还有一些直径小于5m的小土堆,仅显示了土堆的顶部,直径大于20m的大土堆和匙孔形的土堆。因此,据推测,尚未发现一些较小的古代墓葬地,因为古代墓葬地被树木覆盖。作者一直致力于开发一种有效的提取方法,用于使用激光扫描数据对树木覆盖的古墓葬地进行有效的提取。然而,用于从小到大的土墩的稳健提取的滤波方法和阈值是个问题。以此动机为基础,提出了使用金字塔过滤器从较小的土墩到较大的土墩进行有效提取的过滤和阈值化方法。这种方法最引人注目的一点是它能够有效地从越来越小的土丘中提取出来的能力。特别地,所提出的金字塔过滤显示了提取直径小于5m的较小土堆的能力,并且通过该方法新提取了11个土堆。此外,为了进行视觉调查,本文生成了土丘区域的景观动画。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号