Robust disparity estimation in terrain modeling for spacecraft navigation

Navigation and imagery in the orbit, descent, and landing phases during an interplanetary mission require methods that are able to derive the elevation map of a planetary body using remote sensing tools. The authors propose stereovision techniques for this task. An algorithm for correspondence matching, which is one of the crucial steps in automatic terrain modeling, is introduced. It uses well known pyramid-based data structures, but is novel in its direct application of methods from statistical pattern recognition. Feature vectors for correspondence matching and feature selection techniques are used to find optimal features. These include grey-level statistics (mean variance) as well as more sophisticated features derived from operators like local frequency edge gradient or, as an extension, Moravec-, Gabor- or Fourier-features. The applicability of the algorithm in the remote sensing scenario of interplanetary missions is verified using a mockup simulation of the Martian surface