Digital terrain models (DTMs) are simply regular grids of elevation measurements over the land surface. DTMs are mainly extracted by applying the technique of stereo measurements to images available from aerial photography and/or remote sensing. However, numerous geoscience and engineering applications need denser and more accurate DTM data. Collecting additional height data in the field, is either expensive or time consuming. Stereo aerial or satellite imagery is often unavailable and very expensive to acquire. Interpolation techniques are fast and cheap, but have their own inherent difficulties and problems, especially in rough terrain. Shape from shading (SFS) is one of the methods to derive the geometric information about the objects from the analysis of the monocular images. This paper discusses the idea of using the SFS method with single high resolution imagery to optimize the interpolation techniques used in densifying regular grids of heights. The efficiency of the SFS methods was analyzed by trying to reconstruct the 1m DTM from 5m DTM and 1m Ikonos imagery. The three SFS methods were examined, each with five cases of the image (without classification, unsupervised classification, Maximum Likelihood Classification, Mahalanobis Distance Classification and Minimum Distance Classification). Fifteen DTMs were produced and the differences between the original DTM and each DTM were analyzed. Finally, Numerical results are discussed and presented; a few remarks and conclusions are drawn.