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基于无人机航拍路面的拼接算法研究 被引量:10

Research on Stitching Algorithm Based on UAV Based on Aerial Photography
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摘要 为快速得到较大范围且清晰度足够的路面图像,提出一种针对航拍路面图像的拼接算法,可以快速准确处理图像,得到路面的拼接图像,为无人机航拍应用道路交通领域提供便利。路面图像拼接时,图像包含较大的相似区域,导致配准正确率较低,且图像信息量大,拼接时间长。为解决这一问题,本文提出在特征点提取前确定相邻图像的重叠区域,在重叠区域内使用尺度不变特征变换特征点结合稀疏表示匹配的方法,对相邻图像进行配准,随后利用小波变换方法,将图像进行融合,改善拼接效果.经过实验证明,本文方法可以有效处理航拍路面图像,得到效果较好的路面拼接图像。 In order to quickly obtain a wide range of pavement images with sufficient clarity,a stitching algorithm for aerial pavement images is proposed,which can quickly and accurately process the images to obtain the stitched images of the pavement surface so as to provide convenience for the application of unmanned aerial vehicle aerial photography in the field of pavement transportation.When pavement images are stitched,the images contain large similar areas,resulting in a low registration accuracy,a large amount of image information,and a long stitching time.In order to solve this problem,this paper proposes to determine the overlapping area of adjacent images before feature point extraction.Scale-invariant feature transform feature points combined with sparse representation matching method in the overlapping area to register adjacent images.Then,wavelet transform method is used fuse the images to improve the stitching effect.Experimental results prove that the proposed method can effectively process aerial pavement images and obtain better pavement stitching images.
作者 韩建峰 张妍 Han Jianfeng;Zhang Yan(College of Information Engineering,Inner Mongolia University of Technology,Hohhot,Inner Mongolia 010080,China;Inner Mongolia Key Laboratory of Perception Technology and Intelligent Systems,Hohhot,Inner Mongolia 010080,China)
出处 《激光与光电子学进展》 CSCD 北大核心 2020年第20期38-44,共7页 Laser & Optoelectronics Progress
基金 2019年度内蒙古自治区关键技术攻关计划项目(2019GG271) 内蒙古自治区高等学校科学研究重点项目(NJZZ19068)。
关键词 图像处理 图像拼接 稀疏表示 图像配准 图像变换 小波变换 image processing image stitching sparse representation image registration image transformation wavelet transform
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  • 1万发贯.遥感图象数字处理[M].武汉:华中理工大学出版社,1991..
  • 2朱长青.小波分析理论.应用模型与影像分析(博士论文)[M].郑州:解放军测绘学院,1996..
  • 3钱曾波 朱述龙.基于小波变换的图象变焦技术[J].测绘学院学报,1994,(3).
  • 4Cliche F,Bonn F,Teillet P.Integration of SPOT panchromatic channel into its multispectral mode for image sharpness enhancements[J].Photogrammtric Engineering Remote Sensing,1985,46(10):1352-1334.
  • 5Hall D L,Llinas J.An introduction to multisensor data fusion[J].Proceedings of the IEEE,1997,85(1):6-23.
  • 6Genderen C,Pohl J,Van L.Multisensor image fusion in remote sensing:concepts,methods and applications[J].International Journal of Remote Sensing, 1998, 19(5): 823-854.
  • 7Mallat S. A theory for multiresolution signal decomposition: the wavelet representation [J], IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674-693.
  • 8Mallat S, Zhong Siren. Characterization of signals from multiscale edges[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(7): 710-732.
  • 9Li Hui, Manjunath B S, Mitran S K. Multi-sensor image fusion using the wavelet transform [A]. In: Proceedings of First International Conference on Image Processing [C], Austin,Texas, USA, 1994, 1: 51-55.
  • 10Burt P J, Kolczynski R J. Enhanced image capture through fusion[A]. In: Proceedings of 4th International Conference on Computer Vision [C], Berlin, Germany, 1993 : 173-182.

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