Building Change Detection In Very High-Resolution Remote Sensing Image Based On Pseudo-Orthorectification

When using very high-resolution (VHR) remote sensing images acquired at different times to detect building changes, the building positional inconsistencies caused by different satellite imaging angles are an outstanding issue. To tackle this problem, a novel building change detection method based on pseudo-orthorectification (PO) is proposed. First, to determine the building displacement value, a fast line detection method is used to accurately extract the building vertical facade contour lines under the constraint of the Object Space Positioning Consistency (OSPC). Second, the building roof sample selection is automatically conducted under the constraint of building facade contour lines, and the Grab-Cut algorithm is used to extract the roofs combining with corresponding geometric rules. Then, the roof of each building is shifted along the elevation line to its real location. Finally, subtraction is applied to generate the difference image, and reliable change information is obtained by integrating NDVI and shadow information of the building. Three sets of WorldView and QuickBird satellite images are used to compare the proposed method with three state-of-the-art methods. The experimental results show that the average accuracy of the proposed method can reach 92.80%, which is 12.66% higher than that of compared methods.