Seam-line determination via minimal connected area searching and minimum spanning tree for UAV image mosaicking

Abstract

ABSTRACTSeam-line-based image fusion technology is widely used in unmanned aerial vehicle (UAV) image mosaicking for its superiority to effectively avoid the ghosting phenomenon. Existing algorithms typically determine a seam-line by minimizing the sum of the mismatching values on the line. However, the strategy of directly summing the mismatch scores is inadequate because a seam-line segment with significant mismatches, even if it is short, is more visible than a lengthy one with small differences. Seeking the minimal solution also results in these methods having large computation cost. To this end, we propose a novel seam-line determination method based on minimal connected area searching and minimum spanning tree to eliminate observable visual discontinuity and improve the time efficiency. The proposed method first finds the minimal connected area by eliminating occlusions across the overlapping area. It then applies the minimum spanning tree algorithm to find the optimal seam-line. Finally, it searches the seam-line around the equidistant lines to reduce the minimum connected area, thus reducing the computation. The experimental results on various types of UAV images demonstrate that the proposed method achieves excellent performance and competitive computational efficiency relative to the state-of-the-art methods for image mosaicking.