Automatic Extraction and Identification of Lunar Impact Craters Based on Optical Data and DEMs Acquired by the Chang’E Satellites

Craters form the basis for lunar geological stratigraphy and yield significant information on terrain evolution and the history of the solar system. Thus, the recognition of lunar impact craters is an important branch of modern planetary studies. To resolve issues associated with the insufficient and inaccurate extraction of quantitative information about lunar impact craters, this study proposes an algorithm for the automatic extraction and identification of impact craters that is based on CCD stereo camera images and associated digital elevation model (DEM) data that were acquired by the Chang´E satellites. The proposed procedure works by jointly characterizing a crater candidate by means of its 2-D and 3-D features. Specifically, the novel procedure discussed in this paper selects possible crater candidates based on the extraction of geometric features from optical images and improves the final selection using 3-D features that are extracted from the DEM. Additionally, this study addresses for the first time to accurately identify different types of impact craters based on the 2-D and 3-D characteristics of the crater bottoms as well as topographic transects across the craters. The proposed approach is tested on multiple data sets that were acquired by the Chang´E satellites and provides a very high level of accuracy in both the detection and identification phases.