中文摘要：

本文提出一种基于相机自标定和准稠密匹配相结合的星球漫游车的环境地形重构方法，通过SIFT特征点提取、Kruppa方程的相机自标定、准稠密匹配以及三维重构，生成漫游区域的环境地形图。与传统方法相比，该方法首先通过Kruppa方程可以不依赖星球地形地貌场景的几何结构实现车载相机参数的自标定，解决车载相机参数不一致性问题；其次，通过基于SIFT特征点的准稠密匹配能够快速获得更多可靠而准确的匹配点；最后，利用相机参数标定结果和匹配点实现稠密的、高精度的星球漫游车环境地形重构。实验结果证明了该方法的有效性。

英文摘要：

A novel method is presented based on camera self-calibration and quasi-dense match for environmental terrain reconstruction of planetary rover. The terrain map surrounding planetary rover is generated by selecting Scale Invariant Feature Transform （SIFT） point, camera self-calibration using Kruppa equations, quasi-dense match and 3D reconstruction. Firstly, camera parameters can be obtained by camera self-calibration using Kruppa equations without geometrical structure presenting on special scene of the planetary topography and geomorphology. Then, based on SIFT features point, quasi-dense match can achieve more reliable and accurate matching points. Finally, According to the computed results, dense and high precision terrain map of planetary rover can be obtained quickly. The experimental results with simulated environment show the method is effective.