Target Fusion Detection Algorithm Based on ROI and Evidence Theory

Taking advantage of the complementary characteristics in synthetic aperture radar (SAR) and optical images, a military target detection method based on decision fusion of regions of interest (ROI) is proposed. The algorithm firstly extracts ROI from SAR and optical images respectively, and then assigns reliability degrees, which indicated the probability of target, to ROI based on their statistical features and geometric features. Finally, the reliability degrees of the same ROI from two sources are combined by D-S decision level fusion theory before an ultimate detection result is obtained. The method makes good complementary of the advantages of SAR and optical images, which is validated in the experiments with remote sensing image set.