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Fast image stitching of unmanned aerial vehicle remote sensing image based on SURF algorithm

机译:基于冲浪算法的无人空中车辆遥感图像快速图像拼接

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Fast acquisition and processing of effective data sources are a heated topic in remote sensing image processing research. Unmanned aerial vehicle (UAV) remote sensing system has the advantages of maneuverability, rapidity and economical, it has become a hot topic in the world. The study analyzes the characteristics of remote sensing image and the characteristics of UAV remote sensing system and refers a variety of images fast processing algorithms to explore the rapid remote sensing images stitching and rapid information extraction methods. Based on the analysis of the relevant research at home and abroad, this paper draws lessons from some image processing ideas of modern photogrammetry and proposes a fast image stitching method of UAV remote sensing images based on SURF (Speed Up Robust Features) feature description. This method is applied to UAV remote sensing fast image stitching to achieve high-quality UAV remote sensing images for fast and automatic splicing. The stitching speed of this method is much faster than that of SIFT (Scale-invariant feature transform) algorithm. And the splicing effect of this method is satisfactory.
机译:快速采集和处理有效数据源是遥感图像处理研究中的加热主题。无人驾驶飞行器(UAV)遥感系统具有机动性,快速和经济的优势,它已成为世界上的热门话题。该研究分析了遥感图像的特性和UAV遥感系统的特性,是指各种图像快速处理算法,用于探索快速遥感图像拼接和快速信息提取方法。基于对国内外相关研究的分析,本文从现代摄影测量的某些图像处理思想中汲取了课程,并提出了一种基于冲浪(加速鲁棒功能)特征描述的UAV遥感图像的快速图像拼接方法。该方法应用于UAV遥感快速图像拼接,以实现快速和自动拼接的高质量UAV遥感图像。该方法的拼接速度比SIFT(尺度不变特征变换)算法的拼接速度快得多。这种方法的拼接效果令人满意。

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