联合云量自动评估和加权支持向量机的 Landsat 图像云检测

摘要

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.Fi rstly,the ACCA algorithm is used to divide image pixels into cloud pixels,non-cloud pixels and undetermined pixels based on the atmospheric radiation character-istics 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 unde-termined pixels,the cloud detection results of al l 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.%针对云量自动评估算法难以检测 Landsa t 图像中的半透明云问题，提出一种云量自动评估和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，结合陆地卫星 ETM＋图像数据的光谱特性，利用云量自动评估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，利用加权支持向量机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。仿真试验结果表明，该方法既具有云量自动评估算法的云检测优势，还对云量自动评估算法难以识别的半透明云有较好的检测效果。