中文摘要：

本文以四川地震灾区作为典型研究区,尝试在无其他控制点数据时,仅利用小型无人机影像和无人机系统自身记录的辅助数据,进行无人机影像的快速匹配、拼接和纠正处理。首先,对小型无人机获取的影像数据和辅助数据进行了详细分析,然后,将小区域原始影像利用影像匹配算法进行自动拼接,拼接后的分块区域再根据辅助数据进行纠正处理。SIFT算法被运用到无人机影像的匹配中,达到了较好的速度和精度;分块拼接后的成果利用辅助数据的伪中心点进行纠正,相对精度较高,镶嵌结果无视觉错位。最后,将纠正结果和GoogleEarth影像数据叠加进行精度检查,主要标志性地物重叠良好。

英文摘要：

Unmanned Aerial Vehicles（UAV） images quickly processing method without other GCP（Ground Control Point） data is discussed in this paper,and the UAV images of Disaster Areas of Wenchuan Earthquake in Sichuan Province are used as the typical test data source.In the handling progress,only the images and auxiliary data recorded by the UAV system itself are used to stitch and rectify the image mosaics.The main work contains images,which were recorded by digital camera on the UAV and auxiliary data,which were recorded by GPS（Global Positioning Satellite） system on the UAV analyzing,flying area blocking,image auto-stitching after blocking,image rectifying and image mosaic.The image auto-stitching is the key point of the whole research.Firstly,a detailed analysis on UAV images and auxiliary data is done.With the analysis result,many questions are put out,such as the number of images is so large and UAV image distortion is worse than that of traditional photogrammetry.These bring a lot of difficulties to the work,that the normal methods can not be used.Base on this situation,a new strategy is proposed in this paper.That is,in the small area,which is determined by the experiment,the auto-stitching method base on image matching is raised,then the regional images after auto-stitched are corrected according to auxiliary data of UAV.In the image matching progress,SIFT（Scale-Invariant Features Transform） algorithm is applied in order to achieve high efficiency and high precision.Then pseudo center points collected from auxiliary data are used to rectify the regional images.From the result image after stitching and rectifying,a conclusion can be drawn that the relative accuracy is high and the mosaic image is visually dislocation-free.