联合云量自动评估和加权支持向量机的Landsat图像云检测

针对ACCA（云量自动评估）算法难以检测Landsat图像中的半透明云问题，提出了一种ACCA和WSVM（加权支持向量机）相结合的云检测算法．首先根据云在不同波段中的大气辐射特点，结合Landsat ETM+图像数据的光谱特性，利用ACCA算法将图像像元初步分成云像元、非云像元和待定像元，再以云的光谱特性构造特征向量，利用WSVM算法进行待定像元的云层检测，最终获得全部图像的云检测结果．仿真实验结果表明，该方法既具有ACCA算法的云检测优势，还对ACCA算法难以识别的半透明云有很好的检测效果．

Cloud Detection for Landsat Images by Combination of ACCA with WSVM

A cloud detection algorithm combining ACCA (automatic cloud cover assessment) with WSVM (weighted support vector machine) is proposed to solve the problem that ACCA algorithm is difficult to detect the translucent cloud on Landsat images. Firstly, the ACCA algorithm is used to divide image pixels into cloud pixels, non-cloud pixels and undetermined pixels based on the atmospheric radiation characteristics of cloud in different bands and the spectral characteristics of Landsat ETM + image data. Then using the spectral properties of cloud to construct feature vectors, and using WSVM algorithm to detect the undetermined pixels, the cloud detection results of all the images are obtained. Experimental results show that this method not only has the advantages of ACCA cloud detection algorithm, but also has good detection effect for the translucent cloud which is hardly identified by ACCA.