Mismatches Filtering of Unmanned Aerial Vehicle Images Based on Motion Vector Consistency

Fast and efficient mismatches filtering is significant for unmanned aerial vehicle (UAV) image matching. The traditional geometric model-based filtering is time-consuming and may deteriorate when nonrigid transform exists. To extract more reliable correspondences with less running time, filtering mismatches under the guidance of a subset of initial seed matches derived from putative matches is proposed. The method includes three steps: 1) obtain a subset of initial seed matches based on information entropy and range searching; 2) construct a seed kd-tree with initial seed matches to determine the remaining matches according to the consistency of k-nearest neighbors, and then add the true matching point to the seed kd-tree; and 3) repeat step 2 until all remaining putative matches are confirmed. Extensive experiments prove that the proposed method is competitive compared with state-of-the-art methods.