针对典型目标识别问题,提出了一种基于投影寻踪的高光谱目标识别算法。先对高光谱图像进行最小噪声分离变换,计算出本征维度,同时对图像去噪,然后采用信息散度作为投影指标,对投影指标值自适应分割,得到所要提取的波谱曲线,最后用光谱角匹配识别出目标及其位置。高光谱图像验证结果表明,该方法有效地去除了图像噪声,而且能够快速、可靠地提取端元并识别出目标。 Aiming at the problem of typical target recognition, a hyperspectral target recognition algorithm based on projection pursuit is proposed. First of all, the hyperspectral image is transformed with minimum noise, the intrinsic dimension is calculated, meanwhile the image is denoised. Then the information divergence is used as the projection index, and the projection index is adaptively segmented to get the spectral curve to be extracted. Finally, Angle matching identifies the target and its position. Hyperspectral image verification results show that this method can effectively remove the image noise, and can quickly and reliably extract the endmember and identify the target.