An Efficient Approach for Automatic Rectangular Building Extraction From Very High Resolution Optical Satellite Imagery

This letter presents a new approach for rapid automatic building extraction from very high resolution (VHR) optical satellite imagery. The proposed method conducts building extraction based on distinctive image primitives such as lines and line intersections. The optimized framework consists of three stages: First, a developed edge-preserving bilateral filter is adopted to reduce noise and enhance building edge contrast for preprocessing. Second, a state-of-the-art line segment detector called EDLines is introduced for the real-time accurate extraction of building line segments. Finally, we present a graph search-based perceptual grouping approach to hierarchically group previously detected line segments into candidate rectangular buildings. The recursive process was improved through the efficient examination of geometrical information with line linking and closed contour search, in order to obtain more reasonable omission and commission rate in building contour grouping. Extensive experiments performed on VHR optical QuickBird imageries justify the effectiveness and robustness of the proposed linear-time procedure with an overall accuracy of 80.9% and completeness of 87.3%. This method does not require user intervention and thereby has the potential to be adopted in online applications and industrial use in the near future.