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首页> 外文会议>IEEE International Conference on Green Computing and Communications;IEEE International Conference on Cyber, Physical and Social Computing;IEEE International Conference on Internet of Things;IEEE International Conference on Smart Data >A Novel Image Mosaic Method Based on Improved ORB and its Application in Police-UAV
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A Novel Image Mosaic Method Based on Improved ORB and its Application in Police-UAV

机译：基于改进ORB的图像拼接新方法及其在警用无人机中的应用

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摘要

Images acquired by police-UAV (Unmanned Aerial Vehicle) for reconnaissance and forensics need to be stitched in real-time. Image registration affects the quality of image mosaic. For the UAV aerial images with high resolution and rich information, the feature points detected by ORB (oriented FAST and rotated BRIEF) algorithm are unevenly distributed and easy to cluster, which will influence the matching rate and efficiency during image registration. In order to solve the problem, this paper proposes a novel image mosaic method based on improved ORB algorithm. First, a mask is constructed in the image to be registered, and an improved ORB algorithm is adopted to detect and describe feature points. Then, the feature points are matched by Hamming distance and the matched pairs are purified by the Progressive Sample Consensus (PROSAC) algorithm. Finally, the max-flow min-cut algorithm is utilized to determine the best seam-line and the improved Laplacian fusion algorithm is used to eliminate the ghosting, while realizing the seamless splicing of the UAV images. The experimental results show that the proposed method can obtain higher matching rate and efficiency for images with changes of scale, rotation, blur, viewpoint and illumination, and also have good performance in eliminating stitching seam and ghosting.
机译：由警察无人机（UAV）获取的用于侦察和法医的图像需要实时拼接。图像配准会影响图像镶嵌的质量。对于高分辨率，信息量丰富的无人机航拍图像，ORB（定向FAST和旋转BRIED）算法检测到的特征点分布不均，易于聚类，影响图像配准时的匹配率和效率。为了解决该问题，本文提出了一种基于改进的ORB算法的图像拼接方法。首先，在要配准的图像中构造一个遮罩，并采用改进的ORB算法来检测和描述特征点。然后，通过汉明距离对特征点进行匹配，并通过渐进样本共识（PROSAC）算法对匹配的对进行纯化。最后，利用最大流最小割算法确定最佳的接缝线，并使用改进的拉普拉斯融合算法消除重影，同时实现了无人机图像的无缝拼接。实验结果表明，所提出的方法对于缩放，旋转，模糊，视点和照度变化的图像可以获得较高的匹配率和效率，并且在消除缝线和重影方面具有良好的性能。

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