基于轮廓的刚性变换多传感器图像配准

Zhenhua Li, H. Leung
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引用次数: 10

摘要

提出了一种基于轮廓的多传感器图像配准算法。该方法的特点是根据待配准图像中匹配轮廓对的质心和长轴计算配准参数,克服了基于特征的配准技术中控制点检测和对应的困难。假设参考图像和感测图像之间的几何变形遵循刚性变换。分别从参考图像和感测图像中提取显著轮廓。轮廓匹配完成后,将每个开放轮廓的两个端点用线段连接起来,将开放轮廓匹配变为闭合轮廓匹配。然后根据闭合轮廓匹配的质心和长轴角估计配准参数。实际数据实验表明,该算法在多传感器图像配准中效果良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contour-based multisensor image registration with rigid transformation
This paper presents a contour-based multisensor image registration algorithm. The characteristic of this approach is that the registration parameters are calculated according to the centroids and the long axes of matched contour pairs in the images to be registered It overcomes the difficulties of control point detection and correspondence in feature- based registration techniques. The geometrical deformation between the reference and sensed images is assumed to follow a rigid transformation. Salient contours are extracted from the reference and sensed images, respectively. After contour matching, open contour matches are changed to closed contour matches by linking the two endpoints of each open contour together with a line section. Registration parameters are then estimated according to the centroids and the angles of long axes of closed contour matches. Experiments using real data show that the proposed algorithm works well in multisensor image registration.
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