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

Zhengxiang Song; Sicong Liu; Yanmin Jin

doi:10.1117/12.2638482

26 October 2022 An automatic approach for ice-block falls detection in the Martian north polar region

Zhengxiang Song, Sicong Liu, Yanmin Jin

Proceedings Volume 12267, Image and Signal Processing for Remote Sensing XXVIII; 1226709 (2022) https://doi.org/10.1117/12.2638482
Event: SPIE Remote Sensing, 2022, Berlin, Germany

Abstract

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.

Citation Download Citation

Zhengxiang Song, Sicong Liu, and Yanmin Jin "An automatic approach for ice-block falls detection in the Martian north polar region", Proc. SPIE 12267, Image and Signal Processing for Remote Sensing XXVIII, 1226709 (26 October 2022); https://doi.org/10.1117/12.2638482

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available