Dem-based shadow detection and removal for lunar craters

In this paper, we focus on the shadow problem of the lunar surface, which hinders the implementation of visual tasks and visual processing for moon exploration projects. A random walker model is firstly applied to detect the shadowed pixels in lunar craters. Then, the detected shadows are removed by rectifying the illumination coefficients and detail coefficients, which are obtained by using the multi-scale decomposition technique. The proposed algorithm is evaluated on three groups of CCD images and the corresponding DEM data. Satisfactory results, which achieve comparative illumination yet preserve enough details, demonstrate the effectiveness of the proposed algorithm.