Variational methods have been frequently used for surface reconstruction and contour extraction (snakes). We present a surface reconstruction method where we assume the surface composed of two regions of different types of smoothness. One region of the surface models a "lake" (constant height region with uphill borders). It is surrounded by the other background region which is reconstructed using classic surface regularization. The boundary between the two regions, represented by a closed curve is determined with the help of an active contour model. Then the surface is reconstructed by minimizing the energy terms in each region. Minimizing a global energy defined on the couple of unknowns - boundary curve and surface - permits to introduce other forces on the curve. The surface reconstruction and contour extraction tasks are then made together. We have applied this model for segmenting a synthetic Digital Terrain Model (DTM) image which represents a noisy mountain and lake
