轻小型无人机高光谱影像拼接研究  

Light and Small UAV Hyperspectral Image Mosaicking

作　　者：易俐娜[1] 许筱 张桂峰[2,3] 明星 郭文记[2] 李少聪[1] 沙灵玉 YI Li-na;XU Xiao;ZHANG Gui-feng;MING Xing;GUO Wen-ji;LI Shao-cong;SHA Ling-yu(China University of Mining & Technology,Beijing,Beijing 100083,China;Academy of Opto-Electronics,Chinese Academy of Sciences,Beijing 100094,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国矿业大学(北京),北京100083 [2]中国科学院光电研究院,北京100094 [3]中国科学院大学,北京100049

出　　处：《光谱学与光谱分析》2019年第6期1885-1891,共7页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(61405204);中央高校基本科研业务费项目(2011QD03);中国矿业大学(北京)大学生创新训练项目(C201802773);中国科学院战略性先导科技专项(A类)(XDA13020506);中国科学院科研仪器设备研制项目(YJKYYQ20170044)资助

摘　　要：轻小型、低成本无人机(unmanned aerial vehicle,UAV)机载光谱成像仪的快速发展为水质监测、精准农业提供了新的手段。ZK-VNIR-FPG480机载高光谱成像仪是国产仪器,拥有自主产权,影像共有270个波段,光谱范围为400~1 000 nm,光谱分辨率为3 nm,空间分辨率为0.9 m@1 km,成像方式为运动推扫成像,该成像仪的特点是影像之间不存在航向重叠,只存在旁向重叠。它在提供高光谱、高空间分辨率影像的同时也存在着一系列问题:①无人机的狭窄视场限制了每条航带的地面覆盖范围,需要进行航带拼接;②其自带的POS系统定位精度低;③为提高作业效率,航带间的重叠率较低,一般设置在30%左右,为影像拼接增加了困难;④因飞行时受风力、光照以及仪器自身等影响使得每条航带间存在亮度差异,拼接时会出现拼接缝现象。针对上述问题提出一种基于曲面样条函数和相位相关的无人机高光谱影像拼接方法,旨在将无人机拍摄的单条高光谱航带拼接成一幅完整的带有地理坐标的全景图,并实现影像几何和光谱上的匹配。该方法包括以下几个步骤:首先,以正射影像为基准采用曲面样条函数法对高光谱航带进行地理配准,赋予每条航带真实的地理坐标;然后采用局部方差法计算各波段信噪比,取分值最高的波段作为最优波段;再利用该最优波段采用基于2幂子图像的相位相关算法来纠正航带间已经存在的地理空间映射关系,消除航带间存在的错位;最后选用加权平均融合法对相邻航带进行融合,消除航带拼接时因光照、仪器自身等影响所产生的拼接线问题,最终得到带有绝对地理坐标的高光谱全景图。实验使用ZK-VNIR-FPG480机载高光谱成像仪获取大理某地区的高光谱数据进行拼接,结果表明,该拼接方法得到的全景图拼接处没有错位现象,几何位置准确。选取4种典型地物拼接前后的光谱曲线,其曲线�The rapid development of small and low-cost unmanned aerial imaging spectrometer has provided new means for water quality monitoring and precision agriculture.The ZK-VNIR-FPG480 airborne hyperspectral imager is a domestic development instrument with independent property right.The image has a total of 270 bands,the spectral range is 400~1 000 nm,the spectral resolution is 3 nm,and the spatial resolution is 0.9 m@1 km.The imaging method is motion push broom imaging,which is characterized by no overlap between the images and only overlapping.While providing high spectral and high spatial resolution images,it also has a series of problems:①the narrow field of unmanned aerial vehicle(UAV)restricts the coverage of the ground surface of each airstrip,and requires the splicing of flights;②the positioning accuracy of its POS system is low;③In order to improve operational efficiency,the overlap ratio between navigation bands is relatively low,which is generally set at about 30%,making it difficult to image splicing;④Due to the influence of wind,light,and the instrument itself during flight,there is a difference in brightness between each band,and stitching occurs when stitching occurs.This paper proposes a method for splicing UAV hyperspectral images based on surface spline function and phase correlation,aiming at solving the above problems.The aim is to splice a single hyperspectral band taken by UAV into a complete panorama with geographic coordinates,and to achieve image geometry and spectral matching.The method includes the following steps:First,the hyperspectral flight is georeferenced using the surface spline function method with the orthophoto image as the reference,and the real geographic coordinates of each flight are assigned;second,the local variance method is used to calculate the signal-to-noise ratio of each band,and the highest value band is taken as the optimal band;and then the phase correlation algorithm based on the 2 power image is used to correct the existing geographic spatial mapping relation

关 键 词：高光谱影像 影像拼接 曲面样条函数法 信噪比 相位相关法 加权平均融合 

分 类 号：P237[天文地球—摄影测量与遥感]