说明：  为解决无人机高光谱影像图幅较小的问题，通过计算高光谱影像各个波段的峰值信噪比筛选特征波段，基于SIFT算法对筛选出的特征波段提取特征点并对特征点进行匹配，图像拼接过程中利用墨卡托投影纠正图像的变形，同时利用经纬度信息及重投影算法细化高光谱相机参数，从而实现大范围高光谱影像的拼接。为检验拼接高图像的光谱是否 发生畸变，利用光谱角填图、波谱特征拟合分类法及二进制编码３种方法对拼接前后的图像典型地物光谱进行分析。结果表明，拼接前后光谱畸变较小。
(In order to solve the problem of small amplitude image of UAV hyperspectral image. In this paper, the feature band is selected by calculating the peak signal-to-noise ratio (SNR) of each band of the hyperspectral image, and then the feature points are extracted and matched to the selected feature band based on the Scale-invariant Feature Transform (SIFT) algorithm. Mercator image is used to correct the image during the image splicing process at the same time, the parameters of hyperspectral camera are refined by using latitude and longitude information together with the reproj algorithm, and finally the hyperspectral image is spliced. In order to test whether the spectrum of the mosaic image is distorted, Spectral Angle Mapping (SAM), Spectral Feature Fitting (SFF) and Binary Encoding (BE) were used to analyze the typical features of the images before and after splicing, the analysis results show that the spectral distortion is small before and after splicing.)