Automatic detection of urban area from the remote sensing imagery based on improved D-S evidence theory

摘要

Urban area detection from the remote sensing imagery has important significance in dynamic monitoring on the use types of city land and the city development planning. An approach for full-automatic detection of urban area is proposed, which can fuse any number of features. The combination formula of the traditional D-S evidence theory (TDSET) is improved by adding a processing factor for conflicting evidences based on the original fusion function. For the validity of the proposed method, three positive evidences (gradient mean, Harris feature points and spectral homogeneity) as well as one negative evidence (local gradient orientation density) are selected to test three GeoEye images. Experimental results show that the precision of the proposed method achieves 96.89% and its recall is 86.52%, where the recall increases about 50% comparing with the TDSET.