A Novel Lunar Rock Detection Method Combining Multi-Scale Phase Feature Type Maps and Phase Congruency Moment Maps

Accurate lunar rock detection is vital for lunar exploration. However, the existing methods are sensitive to factors such as the uneven lighting and terrain relief. To address these issues, a novel method combining multi-scale phase feature type maps (PFTMs) and phase congruency moment maps (PCMMs) is proposed. Firstly, rock seeds are detected through phase congruency and gradient analysis. Secondly, a strategy called the local scale saliency score (LSSS) is proposed to adaptively estimate the optimal scale layer for candidate rock detection. Within this layer, specifically designed local, global, and contextual (LGC) features are employed to identify the regions of interest (ROIs) for rocks. Subsequently, the process of filtering false positives involves the utilization of geometric metrics and scale feature analysis. Finally, a specially designed edge detector named the bilateral local maximum PCMM-PFTM path is proposed to describe the edges of the rocks. Tests on Chang’E-3 and Chang’E-5 Landing Camera (LCAM) images show the proposed method’s robustness in detecting lunar rocks of varying sizes and reflectance, achieving F1-Scores ranging from 0.919 to 0.947.