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UAV Remote Sensing Image Mosaic Technology Combined with Improved SPHP Algorithm

机译:结合改进的SPHP算法的无人机遥感影像拼接技术

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The paper proposes an improved algorithm, for the problem that SPHP algorithm is not suitable for the UAV Remote sensing image mosaic algorithm because it is susceptible to geomorphic factors, resulting in deformation or ghosting. The algorithm firstly extracts feature points by combining SURF algorithm and Harris algorithm. The obtained feature points are coarsely matched by KNN algorithm, then matched by PROSAC algorithm. Finally, the weight coefficient is introduced to calculate the spatial transformation model of the image overlap region. This model replaces the original spatial model of SPHP algorithm. The ghosting of the image overlap area is reduced, and the stitched image is caused to have a smaller deformation. The final result shows that this improved SPHP algorithm can effectively remove the ghost image of the stitched image and generate better stitching results.
机译:针对SPHP算法易受地貌因素影响,变形或重影的问题,提出了一种不适用于无人机遥感图像拼接算法的改进算法。该算法首先结合SURF算法和Harris算法提取特征点。通过KNN算法对获得的特征点进行粗略匹配,然后通过PROSAC算法进行匹配。最后,引入权重系数来计算图像重叠区域的空间变换模型。该模型替代了SPHP算法的原始空间模型。减少了图像重叠区域的重影,并且使缝合图像具有较小的变形。最终结果表明,该改进的SPHP算法可以有效去除拼接图像中的重影,并产生较好的拼接效果。

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