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We proposed a simple yet effective morphological approach to convert a sparseDigital Elevation Model (DEM) to a dense Digital Elevation Model. Theconversion is similar to that of the generation of high-resolution DEM from itslow-resolution DEM. The approach involves the generation of median contours toachieve the purpose. It is a sequential step of the I) decomposition of theexisting sparse Contour map into the maximum possible Threshold ElevationRegion (TERs). II) Computing all possible non-negative and non-weighted MedianElevation Region (MER) hierarchically between the successive TER decomposedfrom a sparse contour map. III) Computing the gradient of all TER, and MERcomputed from previous steps would yield the predicted intermediate elevationcontour at a higher spatial resolution. We presented this approach initiallywith some self-made synthetic data to show how the contour prediction works andthen experimented with the available contour map of Washington, NH to justifyits usefulness. This approach considers the geometric information of existingcontours and interpolates the elevation contour at a new spatial region of atopographic surface until no elevation contours are necessary to generate. Thisnovel approach is also very low-cost and robust as it uses elevation contours.

Generation of High Spatial Resolution Terrestrial Surface from Low  Spatial Resolution Elevation Contour Maps via Hierarchical Computation of  Median Elevation Regions