Fine 3D reconstruction methods with Gaofen-7 satellite stereo images

GONG Danchao; LIU Songlin; HAN Yilong; ZHANG Wei

doi:10.37188/OPE.20233114.2147

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Fine 3D reconstruction methods with Gaofen-7 satellite stereo images

Information Sciences | 更新时间：2023-08-26

- Fine 3D reconstruction methods with Gaofen-7 satellite stereo images
- Optics and Precision Engineering Vol. 31, Issue 14, Pages: 2147-2159(2023)
- 作者机构：
  
  1.地理信息工程国家重点实验室，陕西西安 710054
  2.西安测绘研究所，陕西西安 710054
  3.山东科技大学测绘与空间信息学院，山东青岛 266590
  4.山东省“3S”工程技术研究中心，山东青岛 266590
- 作者简介：
- 基金信息：
- DOI：10.37188/OPE.20233114.2147
  CLC：
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GONG Danchao, LIU Songlin, HAN Yilong, et al. Fine 3D reconstruction methods with Gaofen-7 satellite stereo images. [J]. Optics and Precision Engineering 31(14):2147-2159(2023)
DOI：

GONG Danchao, LIU Songlin, HAN Yilong, et al. Fine 3D reconstruction methods with Gaofen-7 satellite stereo images. [J]. Optics and Precision Engineering 31(14):2147-2159(2023) DOI： 10.37188/OPE.20233114.2147.

摘要

为了实现高分七号卫星亚米级影像的高精度精细三维重建，针对高分七号卫星前后视线阵相机的成像特点，围绕影像的定向、影像畸变消除、密集匹配方法优化等方面，提出一套完整的精细三维重建方法和流程。利用影像间连接点几何约束关系对有理函数模型进行了二次定向消除系统误差；其次采用一种基于物方投影面的水平纠正方法对原始影像进行纠正，消除了立体像对之间大的倾斜误差；在密集匹配阶段，将全球公开数字高程模型（Digital Elevation Model，DEM）数据作为视差约束，同时引入顾及影像灰度和特征信息的AD-Census作为匹配测度，有效削弱重复纹理引起的匹配错误问题，提升了数字表面模型（Digital Surface Model，DSM）的质量。利用覆盖我国宁夏和新疆某地的两组高分七号的立体影像进行了试验，结果表明本文所提出方法可将相对误差精度由平差前的0.847 pixel和0.725 pixel分别提升到平差后的0.652 pixel和0.593 pixel，相对误差精度最大可提高23.02%，基于物方投影面的水平纠正方法能够显著消除大倾角差异带来的几何畸变，对高分七号卫星影像取得了较好质量的DSM产品，尤其是对于小尺度密集建筑物区域的重复纹理取得了较好的效果。

Abstract

To achieve high-precision and fine 3D reconstruction with the Gaofen-7 satellite sub-meter-level images， this paper proposes a method that focuses on the relative error correction of stereo pairs， image horizontal plane correction， and semi-global matching optimization， forming a fine 3D reconstruction pipeline. First， concerning the relative error in the orientation model of Gaofen-7 stereo images， the geometric constraint relationship of the connection point among images is used to eliminate the systematic error of the rational function model. Second， a horizontal correction method based on the projection plane of the object is used to correct the original image； this eliminates the large inclination error difference between stereo images and provides a better data basis for subsequent processes. In the dense matching stage， global publicly available digital elevation model （DEM） data are used as the disparity constraint. AD-Census， which consider both the grayscale and feature information of the image， is employed as the matching cost metric， addressing the matching error problem caused by repeated texture and improving the digital surface model （DSM） production. The results of experiments conducted using Gaofen-7stereo images covering areas in Ningxia and Xinjiang indicate that the proposed method can improve the relative error accuracy from 0.847 and 0.725 pixels to 0.652 and 0.593 pixels， respectively， representing up to 23.02% improvement. The horizontal correction method based on the projection plane of the object can significantly eliminate the geometric distortion caused by the difference in large inclination angle， and good-quality DSM products can be obtained， especially for the repetitive texture of small-scale dense building areas.

关键词

三维重建有理函数模型影像纠正影像匹配半全局匹配

Keywords

3D reconstructionRational Function Model （RFM）image correctionimage matchingsemi-global matching

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