We propose a three step method to extract buildings from the high-resolution PolSAR data, using both the region-based and edge-based information. Firstly, low-level detectors are employed to provide raw region and edge information of the scene. In the second step, improved region-based building detection results are achieved by fusion of label fields, meanwhile the building profile line segments are extracted under a line Markov random field framework. The last step gives the final building footprint estimates: initial rectangle buildings are defined from the building line segments; by optimizing a surface criterion, the final rectangles are retrieved to fit the region-based building detection results. The effectiveness of this method is demonstrated using the real full PolSAR data.
['Yinghua Wang', 'Florence Tupin', 'Chongzhao Han', 'Jean-Marie Nicolas']
Building Detection from High Resolution PolSAR Data by combining Region and Edge Information