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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]