CGHU-CD: A Contrast-Guided Hierarchical Unsupervised Method for Detecting Martian Anthropogenic Changes

Over the last six decades, Mars exploration missions (both successful and unsuccessful) have inevitably altered the Martian surface and environment. Consequently, accurately detecting non-salient anthropogenic changes resulting from these exploration activities plays an essential role in environmental evaluation. However, precise identification of changed areas and their semantic information on Mars is challenging due to interference from natural changes and complex terrain. To address this, we propose an efficient contrast-guided hierarchical unsupervised method, i.e., CGHU-CD, for sample-free Martian anthropogenic change detection (MACD) using high-resolution orbital images. The proposed approach first performs a global patch-level detection, employing feature description and adaptive thresholding, to maximize the removal of unchanged regions, yielding coarse-grained change candidate pairs. A local pixel-level detection method then exploits the contrastive features of anthropogenic changes, including brightness and texture differences relative to the surrounding Martian background, to progressively enhance change information and refine the detection results. Furthermore, an automatic classification method incorporates inherent object brittleness and size information to distinguish different change types. To evaluate the effectiveness of the designed approach, we constructed a MACD dataset collected from High-Resolution Imaging Science Experiment orbiter images, which include four Mars exploration missions. Extensive experiments comparing our CGHU-CD with seven advanced techniques demonstrate its superior capability in detecting non-salient anthropogenic changes of diverse sizes, shapes, and appearances across varied Mars scenarios. It exceeded these existing unsupervised methods by 2.08% to 78.43% in the F1-score measure. The CGHU-CD also achieved superior classification performance to existing techniques, with an increase of 2.77% to 23.28% in the Kappa value. At last, the sample-free CGHU-CD method exhibited superior potential for detecting anthropogenic changes at the Zhurong landing site across diverse sensors and spatial resolutions.