提出了一种有效针对多光谱遥感影像的云影检测与阴影区域修复方法。基于同一地区时相相近的两幅影像，充分利用碎云及阴影的光谱特性分别对云影区域进行融合增强，然后采用Otsu算法求解最佳阈值自动检测出云及阴影区域，根据云影的出现会引起两幅影像局部相应区域明显的亮度变化，可排除亮地物和水体的影响，建立归一化的云影密度图，在此基础上，采用线性加权组合与光谱直方图匹配相结合的方法对其加以修复，利用SPOT 4影像进行的实验表明其修复效果完全能够满足应用需要。

Clouds and their shadows in remote sensing images bring many troubles to image interpretation and application. It is important to detect and repair these regions rapidly. An efficient method was proposed to detect and repair the unwanted clouds and shadows using two images of the same site acquired in adjacent time. At first, the cloud and shadow regions were enhanced by fusing multi-spectral data and then detected automatically using Otsu’s algorithm. Since the clouds and their shadows will lead to obvious differences in brightness between the two images, false detection of highlighted objects and water regions can be easily discarded, and then the normalized cloud and shadow density map can be built. Linear combination of two images and histogram matching algorithm were adopted to repair the shadow and cloud regions. Experiments on SPOT 4 multi-spectral remote sensing data show impressive results which will benefit several applications.