A Framework for Building Change Detection using Remote Sensing Imagery

Change detection of building from high-resolution remote sensing images is an important and challenging
research field in remote sensing. In this paper a novel technique for building change detection from remote
sensing imagery is presented. First, The Morphological Building Index (MBI) features values are computed
for each of the pair images from our datasets and then change of these two MBI images is measured to
indicate the building change. For evaluation purpose, the experiments are carried on IKONOS and Quick
Bird images. The results show that the proposed technique can attain acceptable correctness rates above
90% with overall errors fewer than 9%. Compared with state-of-the-art methods in building change
detection; the proposed framework is computationally much more efficient while achieving better
performance in terms of correctness, completeness, and quality.