3D lunar craters detection based on stereo matching

In this paper, we focus on the 3D crater detection problem on lunar surface, which helps high-precision spacecraft landing and rover navigation in moon exploration projects. A random structured forests method is firstly applied to detect the 2D edges of craters, and then dense correspondence between CCD stereo images estimates the elevations of craters. Finally, we propose a 3D crater detection model, which is solved by an iterative optimization algorithm with the initial 2D edge. Our method is evaluated on three pairs of stereo images captured by Chang'E-I satellite. Experimental results show that the 3D craters in each pair are quickly and accurately located, which demonstrate the effectiveness and efficiency.