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Lunar surface exploration is increasing rapidly. These exploring satellites provide a large number of high resolution images containing topographical information. The topographical information in lunar surface are craters, ridges, mountains and grabens. Extracting this topographical information manually is time-consuming. Hence, an automatic feature extraction is favored. This paper presents a novel approach using image processing techniques to automatically detect ridges in lunar images. The approaches adopted for this development includes phase symmetry, phase congruency and morphological operations to automatically detect significant ridges. The phase symmetry extracts symmetry features with discontinuities, phase congruency extracts features lying in low contrast regions and morphological operations such as thinning and pruning are used to obtain significant ridges. The proposed novel approach experiments on a test set of different regions. These different region images are obtained from different sensors (LROC, Selene and Clementine) having different spatial resolution and illumination variation. The results obtained are compared with the plan curvature method; and they are evaluated based on true and false detection of ridge pixels. Irrespective of illumination variation and spatial resolution, the proposed approach provides better results than the plan curvature method and its detection rate is approximately 92%. [ABSTRACT FROM AUTHOR]

Abstract: Lunar craters provide ample opportunities to study and understand crater morphology because of their vast numbers. This paper focuses on the topographical mapping of 33 Mare craters (Flat- and Round-floor) of ∼2km diameter, using the SELENE DTM. Each crater was analyzed individually for its slope, regional topography and rim signature. The crater slope analysis revealed a small slope variation between the flat- and round-floor craters, in a similar diameter range, with some overlap between them. In the regional topographical analysis, the impact craters formed on the flat- and sloped-surface were analyzed in detail. The crater profile extracted through the rim crest was compared with its corresponding regional topographic profile (obtained over ∼3crater radii). Four types of crater occurrences were observed: type i, ii and iv craters were formed on sloped surface, whereas type iii craters are formed on a flat surface with an equally raised rim. The occurrences of the rim crest on type i and ii craters are on the topographically elevated side of the terrain. But in type iv craters, the rim crest occurs on the topographically lower side of the terrain. The type iv craters uplifted the topographically lower terrain, which depicts the alteration that had taken place due to the impact. This topographical analysis suggests that the surrounding topography should also be considered for understanding the craters. Finally, from the crater rim signature analysis, it was evident that the prominent V-shaped incisions on the rim are caused due to landslide/slumping and by small impactors. This DTM based simple lunar crater analysis revealed information about the crater association with their surrounding topography and their morphological variations on flat- and sloped- surface. [Copyright &y& Elsevier]

Highlights: [•] Crater detection algorithm to detect craters and extract their contextual information. [•] Round- and flat-floored simple lunar craters classified by their structural profile pattern. [•] Contextual information like ejecta identification and dull/degraded state of crater was detected. [•] Overall algorithm performance: Q ∼75%, precision ∼0.8, FPR∼0.2. [•] Round-floor craters in sub-km range with lesser depth forms major population on lunar surface. [Copyright &y& Elsevier]