Minimal Solvers for 3D Geometry from Satellite Imagery
Minimal Solvers for 3D Geometry from Satellite Imagery
复制标题
卫星图像 3D 几何的最小求解器
DOI：
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发表时间：
2015
期刊：
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通讯作者：
Jan
中科院分区：
文献类型：
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作者：
Enliang Zheng;Ke Wang;Enrique Dunn;Jan
我们提出了两种全新的最小二乘解算器，推动了卫星图像处理领域的技术发展。我们的方法高效且不依赖于预先存在的复杂逆映射函数来关联二维图像坐标与三维地形。我们的第一种解算器改进了卫星图像的立体匹配问题，能够提供精确的图像到目标空间的映射（此前的方法并不准确）。我们的第二种解算器为三维点三角测量提供了一种新颖的机制，与先前技术相比，其鲁棒性和准确性都有所提升。鉴于卫星图像的实用性和普遍性，我们所提出的方法能够在各种现有及未来的应用中取得更好的成果。
We propose two novel minimal solvers which advance the state of the art in satellite imagery processing. Our methods are efficient and do not rely on the prior existence of complex inverse mapping functions to correlate 2D image coordinates and 3D terrain. Our first solver improves on the stereo correspondence problem for satellite imagery, in that we provide an exact image-to-object space mapping (where prior methods were inaccurate). Our second solver provides a novel mechanism for 3D point triangulation, which has improved robustness and accuracy over prior techniques. Given the usefulness and ubiquity of satellite imagery, our proposed methods allow for improved results in a variety of existing and future applications.