  Nowadays dense stereo matching has become one of the dominant tools in 3D
reconstruction of urban regions for its low cost and high flexibility in
generating dense 3D points. However, state-of-the-art stereo matching
algorithms usually apply a semi-global matching (SGM) strategy. This strategy
normally assumes the surface geometry pieceswise planar, where a smooth penalty
is imposed to deal with non-texture or repeating-texture areas. This on one
hand, generates much smooth surface models, while on the other hand, may
partially leads to smoothing on depth discontinuities, particularly for
fence-shaped regions or densely built areas with narrow streets. To solve this
problem, in this work, we propose to use the line segment information extracted
from the corresponding orthophoto as a pose-processing tool to sharpen the
building boundary of the Digital Surface Model (DSM) generated by SGM. Two
methods which are based on graph-cut and plane fitting are proposed and
compared. Experimental results on several satellite datasets with ground truth
show the robustness and effectiveness of the proposed DSM sharpening method.
