Putri, ARD;
Sidiropoulos, P;
Muller, JP;
(2019)
Anomaly detection performance comparison on anomaly-detection based change detection on martian image pairs.
In: Vosselman, G and Oude Elberink, SJ and Yang, MY, (eds.)
Proceedings of the ISPRS Geospatial Week 2019.
(pp. pp. 1437-1441).
International Society of Photogrammetry and Remote Sensing (ISPRS): Enschede, The Netherlands.
Preview |
Text
Putri_isprs-archives-XLII-2-W13-1437-2019.pdf - Published Version Download (937kB) | Preview |
Abstract
The surface of Mars has been imaged in visible wavelengths for more than 40 years since the first flyby image taken by Mariner 4 in 1964. With higher resolution from orbit from MOC-NA, HRSC, CTX, THEMIS, and HiRISE, changes can now be observed on high-resolution images from different instruments, including spiders (Piqueux et al., 2003) near the south pole and Recurring Slope Lineae (McEwen et al., 2011) observable in HiRISE resolution. With the huge amount of data and the small number of datasets available on Martian changes, semi-automatic or automatic methods are preferred to help narrow down surface change candidates over a large area. To detect changes automatically in Martian images, we propose a method based on a denoising autoencoder to map the first Martian image to the second Martian image. Both images have been automatically coregistered and orthorectified using ACRO (Autocoregistration and Orthorectification) (Sidiropoulos and Muller, 2018) to the same base image, HRSC (High-Resolution Stereo Camera) (Neukum and Jaumann, 2004; Putri et al., 2018) and CTX (Context Camera) (Tao et al., 2018) orthorectified using their DTMs (Digital Terrain Models) to reduce the number of false positives caused by the difference in instruments and viewing conditions. Subtraction of the codes of the images are then inputted to an anomaly detector to look for change candidates. We compare different anomaly detection methods in our change detection pipeline: OneClassSVM, Isolation Forest, and, Gaussian Mixture Models in known areas of changes such as Nicholson Crater (dark slope streak), using image pairs from the same and different instruments.
Type: | Proceedings paper |
---|---|
Title: | Anomaly detection performance comparison on anomaly-detection based change detection on martian image pairs |
Event: | ISPRS Geospatial Week 2019, 10-14 June 2019, Enschede, The Netherlands |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.5194/isprs-archives-XLII-2-W13-1437-2019 |
Publisher version: | https://doi.org/10.5194/isprs-archives-XLII-2-W13-... |
Language: | English |
Additional information: | © Authors 2019. CC BY 4.0 License. The Archives are open access publications, they are published under the Creative Common Attribution 4.0 License, see publications.copernicus .org/for_authors/license_and_copyright.html for details. |
Keywords: | change detection, Martian surface dynamics, mars, machine learning |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics |
URI: | https://discovery.ucl.ac.uk/id/eprint/10077612 |
Archive Staff Only
![]() |
View Item |