提出了一种基于最小噪声分离的约束能量最小化亚像元目标探测方法。利用最小噪声分离变换，降低高光谱遥感影像的维数，同时分离高光谱遥感影像中的噪声。利用约束能量最小化方法对低维数据进行亚像元目标探测，避免了求解影像虚拟维数和病态矩阵求逆的问题。实验结果表明，该方法可以很好地抑制噪声的影响，亚像元目标探测率较高，是一种快速有效的高光谱遥感影像亚像元目标探测方法。

This paper presents a constrained energy minimization method of sub-pixel target detection for hyper-spectral imageries based on minimum noise fraction (MNF-CEM). In this method, minimum noise fraction (MNF) reduces the dimension of the hyper-spectral imageries and separates the noise from the hyper-spectral imageries. Then constrained energy minimization method (CEM) is used to detect the sub-pixel targets in the imageries of low dimension to void the computations of ill-conditional matrix inverse and virtual dimension of the hyper-spectral imageries. Experiments show that this method can restrain the influence of noise and is an effective method of sub-pixel target detection for hyper-spectral imageries.