The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W1, 119–124, 2017
https://doi.org/10.5194/isprs-archives-XLII-3-W1-119-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W1, 119–124, 2017
https://doi.org/10.5194/isprs-archives-XLII-3-W1-119-2017

  25 Jul 2017

25 Jul 2017

FUSION OF MULTI-SCALE DEMS FROM DESCENT AND NAVCM IMAGES OF CHANG’E-3 USING COMPRESSED SENSING METHOD

M. Peng, W. Wan, Z. Liu, and K. Di M. Peng et al.
  • State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Keywords: DEM fusion, compressed sensing, landing site mapping

Abstract. The multi-source DEMs generated using the images acquired in the descent and landing phase and after landing contain supplementary information, and this makes it possible and beneficial to produce a higher-quality DEM through fusing the multi-scale DEMs. The proposed fusion method consists of three steps. First, source DEMs are split into small DEM patches, then the DEM patches are classified into a few groups by local density peaks clustering. Next, the grouped DEM patches are used for sub-dictionary learning by stochastic coordinate coding. The trained sub-dictionaries are combined into a dictionary for sparse representation. Finally, the simultaneous orthogonal matching pursuit (SOMP) algorithm is used to achieve sparse representation. We use the real DEMs generated from Chang’e-3 descent images and navigation camera (Navcam) stereo images to validate the proposed method. Through the experiments, we have reconstructed a seamless DEM with the highest resolution and the largest spatial coverage among the input data. The experimental results demonstrated the feasibility of the proposed method.