Seamline Optimization Based on Triangulated Irregular Network of Tiepoints for Fast UAV Image Mosaicking

Abstract

UAV remote sensing is suitable for urgent image monitoring and periodic observation of an area of interest. To observe a target area using UAVs, many images must be acquired because of the narrow image coverage of UAVs. To increase the efficiency of UAV remote sensing, UAV mosaicking is used to create a single image from multiple UAV images. In order to maintain the strength of rapid UAV deployment, UAV mosaicked images have to be quickly generated through image-based mosaicking techniques. In addition, it is necessary to improve the mosaic errors of image-based techniques that often occur in contrast to terrain-based techniques. Relief displacement is a major source of mosaic error and can be detected by utilizing a terrain model. We have proposed an image-based mosaicking technique utilizing TIN, which is a model that can represent terrain with discontinuously acquired height information of ground points. Although the TIN is less accurate than DSM, it is simpler and faster to utilize for image mosaicking. In our previous work, we demonstrated fast processing speed of mosaicking using TIN-based image tiepoints. In this study, we improve the quality of image-based mosaicking techniques by optimizing seamline-based TIN geometry. Three datasets containing buildings with large relief displacement were used in this study. The experiment results showed that the TIN based on the proposed method improved the mosaic error caused by relief displacement significantly.

Keywords

• triangulated irregular network
• seamline optimization
• relief displacement
• error-prone region