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激光雷达辅助下的多相机隧道图像拼接

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由于隧道图像纹理单一,匹配特征少,导致图像拼接结果不理想.同时,由于相机畸变的存在,每个CCD相机拍摄图像在边缘地区的形变最大,而拼接处也正好在那个区域,因此直接对整个图像进行整体转换后拼接会出现比较严重的拼接错误现象.为此,本文引入激光雷达,依据其提供的距离信息模拟隧道面,并借助相机内外参将平面图像映射至模拟隧道面,在物方完成图像拼接.借助贝叶斯优化(Bayesian optimization,BO)算法,以最大化相邻相机物方重叠区图像的相似度为目标,迭代优化激光雷达和CCD相机之间的坐标系转换关系,实现激光辅助的隧道图像的拼接.实验结果证明了该方法的有效性.
Multi-camera Tunnel Image Stitching Aided by LiDAR
The tunnel image has simple texture,few match-ing features,therefore the stitching result based on feature matching is not ideal. At the same time,due to the existence of camera distortion,the image taken by each CCD camera has the greatest deformation in the edge areawhere the stitch-ing place is also there. As a result,there will be serious stitch-ing errors with the entire transformed image. To this end,Li-DAR is involved to simulate the tunnel surface according to the distance information provided by it. Then the camera's in-ternal and external parameters are used to map the image to the simulated tunnel surface,thus image stitching on the ob-ject side is completed. With the help of Bayesian optimization (BO) algorithm,with the goal of maximizing the similarity of the images of adjacent camera object overlaps,the coordinate system conversion relationship between Lidar and CCD cam-eras is iteratively optimized to realize the laser-assisted stitch-ing of tunnel images. The experimental results demonstrate the effectiveness of the method.

image stitchingCCD cameraBayesian optimization algorithmLiDAR

李亚楠、黄玉春

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武汉大学遥感信息工程学院,湖北武汉,430079

图像拼接 CCD相机 贝叶斯优化算法 激光雷达

国家自然科学基金

41671419

2024

测绘地理信息
武汉大学

测绘地理信息

CSTPCD
影响因子:0.563
ISSN:1007-3817
年,卷(期):2024.49(3)
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