Building Extraction from High Resolution Remote Sensing Image by Attribute Filtering and Context Analysis

Traditional object extraction methods encounter new challenges as the spatial resolution of remote sensing image increases. For the purpose of building extraction in that circumstance, a new method combining both attribute filtering and context analysis is proposed in this paper. Firstly, attribute filters are performed on the object level, which is defined by the connected pixels with similar attribute. Secondly, according to the prior knowledge of buildings and shadows, preliminary regions are extracted as the building candidates. Thirdly, the context between building and shadow is considered, which leads to the aspect angle, relative position and central distance criteria for the confirmation of buildings from the building candidates. Results on both of the residential and industrial regions demonstrate that the proposed method is effective for building extraction and performs better than the traditional methods.