Efficient registration algorithm for UAV image sequence

Baojie Fan, Yingkui Du, Yandong Tang
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引用次数: 1

Abstract

This paper presents a fast and efficient image registration algorithm for UAV image sequence. The proposed algorithm consists of three main steps: feature extraction, feature point tracking, and homography matrix estimation. According to the comparison with different feature points, we choose the KLT feature and track them during the consecutive images. With the correct tracked feature points, the Total Least Squares (TLS) method is used to estimate homography matrix between two consecutive images, and then the multi-view constraint is used to refine the result and reduce the accumulative error in the image sequence. This method is robust and with less iteration times. Experiments on different image sequences indicate that our method has satisfactory image registration results with the average time 0.3s.
无人机图像序列的高效配准算法
提出了一种快速高效的无人机图像序列配准算法。该算法包括三个主要步骤:特征提取、特征点跟踪和单应性矩阵估计。通过与不同特征点的比较,选择KLT特征,并在连续图像中对其进行跟踪。在正确跟踪特征点的基础上,利用总最小二乘(TLS)方法估计两幅连续图像之间的单应性矩阵,然后利用多视图约束对结果进行细化,减小图像序列中的累积误差。该方法鲁棒性好,迭代次数少。在不同图像序列上的实验表明,该方法具有较好的配准效果,平均配准时间为0.3s。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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