Abstract
Abstract. As the spread of the error and accumulation often lead to distortion or failure of image mosaic during the multi-view UAV (Unmanned Aerial Vehicle) images stitching. In this paper, to solve the problem we propose a mosaic strategy to construct a mosaic ring and multi-level grouping parallel acceleration as an auxiliary. First, the input images will be divided into several groups, each group in the ring way to stitch. Then, use SIFT for matching, RANSAC to remove the wrong matching points. And then, calculate the perspective transformation matrix. Finally weaken the error by using the adjustment equation. All these steps run between different groups at the same time. By using real UAV images, the experiment results show that this method can effectively reduce the influence of accumulative error, improve the precision of mosaic and reduce the mosaic time by 60 %. The proposed method can be used as one of the effective ways to minimize the accumulative error.
Highlights
According to the low cost, high flexibility and less limited by weather and the other characteristics, UAV has been an important way of acquiring data in measuring, GIS and remote sensing
The mosaic process is divided into several levels, which consists of multiple sets of adjacent images, and two adjacent images in each group will be cut into four sub-images with overlap areas, between the two images using the feature-based image mosaic algorithm, and stitch the four images to ring successively, use the adjustment model of the image transformation model to eliminate the error, after these the model will be re-brought into the mosaic process to complete the mosaic before the real stitch of the two images
The SIFT feature is extracted from the two input images and perform the image matching; use random sampling consistency (RANSAC) for removal of mismatch.; The perspective transformation matrix is used as the relationship between the images
Summary
According to the low cost, high flexibility and less limited by weather and the other characteristics, UAV has been an important way of acquiring data in measuring, GIS and remote sensing. One of the most influential factors for mosaic is the existence of accumulated errors By its type it can be divided into two types. We proposed a multi-core parallel ring mosaic algorithm for multi-view UAV to illustrate problem above. The mosaic process is divided into several levels, which consists of multiple sets of adjacent images, and two adjacent images in each group will be cut into four sub-images with overlap areas, between the two images using the feature-based image mosaic algorithm, and stitch the four images to ring successively, use the adjustment model of the image transformation model to eliminate the error, after these the model will be re-brought into the mosaic process to complete the mosaic before the real stitch of the two images. The method can effectively reduce the impact of accumulative error, and greatly reduce the operation time
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