摘要
为了利用航天飞机雷达地形测绘任务数字高程模型(SRTM DEM)与先进星载热反射和反辐射仪数字高程模型(ASTER DEM)的互补信息,提出基于小波分析的多源DEM数据融合方法,以我国秦岭典型高山峡谷地貌类型区为试验样区,选取相同位置的SRTM DEM与ASTER DEM数据,通过重采样、数据配准等步骤形成融合数据源;对小波分解的低频系数作基于邻域像素关联性的融合,高频系数采用像素点绝对值取大的融合,生成融合DEM。并把融合前与融合后的数据分别与1∶5万高程库数据作精度比较,总体统计与抽样检查表明融合DEM精度较源数据均得到了提高。该融合技术为应用SRTM DEM与ASTER DEM生成精度和可靠性更高的DEM产品提供了可行方案。
In order to utilize the complementary information, the multi-DEM fusion by wavelet analysis is presented. The typical physiognomy character in QinLing, which contains high mountain and valley, is selected as experiment area. And the corresponding DEM data of SRTM DEM and ASTER DEM are prepared. The data are preprocessed by re-sampling and co-registered, then the low frequency coefficient of wavelet is fused with neighborhood pixel correlative strategy, and the high frequency coefficient of wavelet is fused with choosing the point of larger absolute value, the fused DEM is produced. The precision of data before and after fusion are compared with 1： 50000 DEM respectively. The results of the collectivity statistic and spot check show that the precision of fusion DEM has improved relative to the original DEM. An effective and reliable method for DEM product from SRTM DEM and ASTER DEM is provided through the wavelet analysis fusion.
出处
《测绘科学技术学报》
CSCD
北大核心
2014年第4期388-392,共5页
Journal of Geomatics Science and Technology
基金
国家自然科学基金项目(41271447)
地理信息工程国家重点实验室基金项目(SKLGIE2013-M-4-4)
关键词
小波分析
低频融合
高频融合
预处理
融合规则
数字高程模型
wavelet analysis
low frequency fusion
high frequency fusion
preprocess
fusion formulae
DEM
