This paper presents an automatic classification algorithm of Mars surface lineament structure based on Resnet50 in DEM (digital elevation model) data. This work aims to reduce the time spent by planetary researchers on the collection of lineament structure samples, so as to concentrate on scientific research based on lineament structure data. This method avoids the problems that traditional DTA (digital terrain analysis) technology can only be used locally and the judgment threshold is difficult to set due to the large differences in Mars around the planet. The highest accuracy of crater is 98.15%, the highest accuracy of dorsum is 100%, the highest accuracy of Vallis is 94.44%, and the highest total accuracy is 87.96%.
The automatic recognition algorithm of lunar terrain is one of the hot topics in recent years. The algorithm which single use CCD or DEM data as data source can’t get a satisfactory result. Some algorithms combine CCD and DEM data sources and make terrain identification in time domain. The recognition rate of these algorithms is improved, but the time efficiency is not satisfactory. In order to solve the above problems, a fast terrain recognition algorithm based on wavelet domain be proposed. in this paper.
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