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首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
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A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM

机译:基于改进的冲浪算法的无人空中车辆遥感图像快速登记的新方法

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摘要

Remote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregular overlap, etc. How to obtain a large regional map quickly becomes a major obstacle to UAV remote sensing application. In this paper, a new method of fast registration of UAV remote sensing images was proposed to meet the needs of practical application. This paper used Progressive Sample Consensus (PROSAC) algorithm to improve the matching accuracy by removed a large number of mismatching point pairs of remote sensing image registration based-on SURF (Speed Up Robust Feature) algorithm, and GPU (Graphic Processing Unit) was also used to accelerate the speed of improved SURF algorithm. Finally, geometric verification was used to achieve mosaic accuracy in survey area. The number of feature points obtained by using improved SURF based-on PROSAC algorithm was only 9.5% than that of SURF algorithm. Moreover, the accuracy rate of improved method was about 99.7%, while the accuracy rate of improved SURF algorithm was increased by 8% than SURF algorithm. Moreover, the improved running time of SURFGPU algorithm for UAV remote sensing image registration was a speed of around 16 times than SURF algorithm, and the image matching time had reached millisecond level. Thus, improved SURF algorithm had better matching accuracy and executing speed to meet the requirements of real-time and robustness in UAV remote sensing image registration.
机译:遥感系统安装在UAV(无人驾驶飞行器)上,可以获得清晰的图像和高分辨率的航拍照片。它具有灵活性,便利性和全职工作能力的优点。然而,诸如小的覆盖区域,大数,不规则重叠等的诸如诸如小的覆盖区域的若干问题。如何获得大型区域地图,将大型区域映射快速成为UAV遥感应用的主要障碍。在本文中,提出了一种新的UAV遥感图像快速登记方法,以满足实际应用的需求。本文使用了逐行采样共识(PROSAC)算法来提高匹配精度,通过除去大量不匹配点对基于冲浪(加速鲁棒特征)算法的大量不匹配点对,而GPU(图形处理单元)也是如此用于加速改进的冲浪算法的速度。最后,使用几何验证来实现调查区的马赛克精度。通过基于基于改进的冲浪的PROSAC算法获得的特征点数仅为9.5%而不是冲浪算法。此外,改进方法的精度率约为99.7%,而改善的冲浪算法的精度率比冲浪算法增加了8%。此外,对于UAV遥感图像配准的改进的SURDGPU算法的运行时间是比冲浪算法约为16次的速度,图像匹配时间达到毫秒。因此,改进的冲浪算法具有更好的匹配精度和执行速度,以满足UAV遥感图像配准中实时和鲁棒性的要求。

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