期刊文献+

小基高比立体测绘仿真与分析 被引量:2

Simulation Analysis of Small-baseline Stereo Surveying
下载PDF
导出
摘要 在航天测绘时,小基高比立体测绘可以较好地避免大基高比的不利因素,有效减弱遮挡、辐射差异、几何畸变和阴影等因素对测绘精度的影响,在城市立体测绘中具有更多的优势。小基高比立体测绘需要对基高比数据值的优化设计进行研究,文章通过仿真分析了影响小基高比立体测绘高程精度的主要因素,搭建了不同密度和高度建筑物的场景,进行了不同基高比和噪声的仿真成像,最终结果表明,基高比、场景、遮挡以及噪声的不同均会对测绘精度产生影响;当地物目标高程越高、场景越复杂时,其最优基高比越小,而由噪声造成的误差越大。 A small-baseline stereo configuration can alleviate the problem caused by wide-baselines. Small-baseline can reduce effectively the influences on survey accuracy of occlusion, radiation difference, geometric distortion and shading, which is much meaningful for metropolis stereo surveying. It is mecessary to study the optimization of baseline. A computer simulation experiment is introduced in this paper, to study the main factors that influence the accuracy of the elevation. The scence with buildings of different heights and densities is obtained to study the noise sensibility by adding independent white noises and the algorithm behavior depending on the baseline. The simulation results show that the different baseline, scene, shading and noise all can influence survery accuracy, and the optimum baseline will be small and noise error large when the earth object DEM is high and the scene complicated.
出处 《航天返回与遥感》 北大核心 2016年第5期95-101,共7页 Spacecraft Recovery & Remote Sensing
基金 国家重大科技专项工程
关键词 小基高比 立体测绘 仿真分析 航天遥感 small-baseline stereo surveying simulation analysis space remote sensing
  • 相关文献

参考文献4

二级参考文献41

  • 1牛力丕,毛士艺,陈炜,焦静.基于长边缘相关和一致性检测的多传感器图像配准方法[J].信号处理,2005,21(2):115-119. 被引量:3
  • 2罗三定,陈海波.基于区域增长的自适应窗口立体匹配算法[J].中南大学学报(自然科学版),2005,36(6):1042-1047. 被引量:10
  • 3Delon J.Fine comparison of images and other problems[D].Paris:ENS Cachan.Mathematics Department,2004:89-108.
  • 4Facciolo G.Variational adhesion correction with image based regularization for digital elevation models[D].Montevicleo:University of the Republic.Engineering College,2005:37-49.
  • 5Delon J,Rouge B.Small baseline stereovision[J].Journal of Mathematical Imaging and Vision,2007,28(3):209-223.
  • 6Igual L,Preciozzi J,Garrido L,et al.Automatic low baseline stereo in urban areas[J].Inverse Problems and Imaging,2007,1(2):319-348.
  • 7Morgan G L K,LIU Jian-guo,YAN Hong-shi.Sub-pixel stereo matching for DEM generation from narrow baseline stereo imagery[C]//Proceedings of International Geoscience and Remote Sensing Symposium.Boston:IEEE,2008:1284-1287.
  • 8Sabater N,Blanchet G,Moisan L,et al.Review of low-baseline stereo algorithms and benchmarks[C]//Proceedings of Image and Signal Processing for Remote Sensing XVI.Toulouse:IEEE,2010:1-12.
  • 9Morgan G L K,LIU Jian-guo,YAN Hong-shi.Precise subpixel disparity measurement from very narrow baseline stereo[J].IEEE Transactions on Geoscience and Remote Sensing,2010,48(9):3424-3433.
  • 10Aujol J F.Some first-order algorithms for total variation based image restoration[J].Mathematical Imaging and Vision,2009,34(3):307-327.

共引文献26

同被引文献19

引证文献2

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部