Analysing high resolution digital Mars images using machine learning ...

• Main Authors: Gergácz, Mira, Kereszturi, Ákos
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: arXiv 2023
• Subjects: Earth and Planetary Astrophysics astro-ph.EP; Instrumentation and Methods for Astrophysics astro-ph.IM; Machine Learning cs.LG; Image and Video Processing eess.IV; FOS Physical sciences; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Ice cap
• Online Access: https://dx.doi.org/10.48550/arxiv.2305.19958; https://arxiv.org/abs/2305.19958

The search for ephemeral liquid water on Mars is an ongoing activity. After the recession of the seasonal polar ice cap on Mars, small water ice patches may be left behind in shady places due to the low thermal conductivity of the Martian surface and atmosphere. During late spring and early summer, these patches may be exposed to direct sunlight and warm up rapidly enough for the liquid phase to emerge. To see the spatial and temporal occurrence of such ice patches, optical images should be searched for and checked. Previously a manual image analysis was conducted on 110 images from the southern hemisphere, captured by the High Resolution Imaging Science Experiment (HiRISE) camera onboard the Mars Reconnaissance Orbiter space mission. Out of these, 37 images were identified with smaller ice patches, which were distinguishable by their brightness, colour and strong connection to local topographic shading. In this study, a convolutional neural network (CNN) is applied to find further images with potential ...