CAJ | 학술논문

光学卫星遥感影像自动云检测是卫星产品生产系统的一个重要环节。利用资源三号卫星编目生成的浏览图，采用树状判别结构进行云检测，对浏览图进行分块，提取子块图像的特征进行云地分类。由于云类和地物类过于繁杂，且浏览图的分辨率较低，传统通过图像特征对云地进行分类的算法有很大的局限性，针对这一问题，本文提出了在分类之前对原始的子块图像进行增强处理，扩大云和地物的纹理差异，然后以二阶矩、一阶差分等作为云地分类的图像特征，并在多尺度空间内进行特征延拓，经过综合分析估计云在影像中的比例。该云检测算法应用于资源三号卫星应用系统工程，实际测试结果表明，该算法能够较好地提升云量检测的准确率。
광학위성요감영상자동운검측시위성산품생산계통적일개중요배절。이용자원삼호위성편목생성적류람도，채용수상판별결구진행운검측，대류람도진행분괴，제취자괴도상적특정진행운지분류。유우운류화지물류과우번잡，차류람도적분변솔교저，전통통과도상특정대운지진행분류적산법유흔대적국한성，침대저일문제，본문제출료재분류지전대원시적자괴도상진행증강처리，확대운화지물적문리차이，연후이이계구、일계차분등작위운지분류적도상특정，병재다척도공간내진행특정연탁，경과종합분석고계운재영상중적비례。해운검측산법응용우자원삼호위성응용계통공정，실제측시결과표명，해산법능구교호지제승운량검측적준학솔。
Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products .For the browse images cataloged by ZY‐3 satellite , the tree discriminate structure is adopted to carry out cloud detection .The image was divided into sub‐images and their features were extracted to perform cl assification between clouds and grounds .However ,due to the highcomplexityofcloudsandsurfacesandthelowresolutionofbrowseimages,thetraditionalclassifica‐tion algorithms based on image features are of great limitations .In view of the problem ,a prior enhance‐ment processing to original sub‐images before classification was put forward in this paper to widen the texture difference between clouds and surfaces .Afterwards ,with the secondary moment and first difference of the images ,the feature vectors were extended in multi‐scale space ,and then the cloud proportion in the image was estimated through comprehensive analysis .The presented cloud detection algorithmhas already been applied to the ZY‐3 application system project ,and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly .