An automatic approach for ice-block falls detection in the Martian north polar region

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This paper proposes a novel coarse-to-fine ice-block falls detection approach based on the YOLO-V4 network and a postprocessing strategy by considering the illumination properties (i.e., adjacent distance, direction, area ratio of ice-block and shadows) of the considered ice-block targets. The proposed approach mainly consists of two steps: 1) Coarse detection of ice-block falls based on the YOLO-V4 network. 2) Extraction of the illumination properties of ice-block targets, and refine the initial detection results based on the post-processing strategy. By taking the edge of the Boreum Planum in Mars Arctic as a research region where presents frequent ice-block falls activity, the HiRISE (High Resolution Imaging Science Experiment) image was used to verify the reliability of the proposed approach. Note that in this work we only focused on the ice-block targets whose length and width are larger than 0.5m (2 pixels in the HiRISE image). Final obtained experimental results confirmed the effectiveness of the proposed approach for identifying the ice-block falls activity over large Martian areas at both local and global scales.