针对非线性混合的高光谱图像目标检测问题，在核信号空间正交投影法（KSSP）的基础上，提出了一种光谱和空间信息结合的组合核信号空间正交投影方法（CKSSP）。分别基于边缘序和像元距离为序尺度函数的导出序将灰度形态变换扩展到多值图像空间中的形态变换，利用多结构元素组合的扩展数学形态学方法提取高光谱图像的空间信息。根据核函数定义，结合光谱信息和空间信息构造出组合核函数并加以证明，通过组合核信号空间正交投影实现目标检测。该方法在充分利用光谱信息的同时，合理利用了空间信息。仿真数据实验结果表明CKSSP的均方根误差比KSSP小0.03，真实高光谱图像数据实验和ROC曲线均表明CKSSP目标检测结果优于KSSP。

In the base of kernel signature space orthogonal projection (KSSP), a composite kernel signature space orthogonal projection (CKSSP) technique, which combines spectral information with spatial information, is proposed for target detection in nonlinearly mixed hyperspectral imagery. The grey mathematical morphological transform is extended into multivariate mathematical morphological transform based on marginal ordering and reduced ordering, respectively. The pixel distance is used as ordering scale function to establish reduced ordering. Extended mathematical morphological method with multi-structure elements is used to extract spatial information of hyperspectral images. Combining the spectral and spatial information, the composite kernel function is constructed and improved according to kernel function definition. Target is detected by CKSSP. The proposed method not only sufficiently applies the spectral information, but also effectively takes into account the spatial information. Experimental results of simulated data demonstrate that root mean square error of CKSSP is 0.03 less than that of KSSP, Experimental results of real data and the receiver operating characteristic curves show that CKSSP approach slightly outperforms the KSSP method in target detection.