Logistic回归模型在卫星云图云检测中的应用  

Application of Logistic regression method in cloud detection of satellite image

作　　者：费文龙[1,2] 吕红[2] 韦志辉[1] 

机构地区：[1]南京理工大学计算机科学与技术学院,南京210094 [2]南京信息工程大学数理学院,南京210044

出　　处：《计算机工程与应用》2012年第4期18-21,28,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61071146);国家自然科学基金(青年科学基金)(No.60802039);南京理工大学自主科研项目(No.2010ZYT070)

摘　　要：云的自动检测和分类识别是所有卫星遥感资料应用的第一个步骤。基于Logistic回归模型的云图处理方法被用于FY-2C卫星云图的处理。利用逐步回归方法对云图的灰度及纹理特征进行提取,并计算出每个特征的回归系数;利用提取的特征进行云检测实验。将实验结果与地面观测资料进行对比,表明Logistic回归模型对云图处理是有效的,并且与传统的动态阈值分割方法相比,云检测的效果更好。Automatic cloud detection is the first step of using the remote sensing data. In this study, a novel cloud detection method based on Logistic regression model is proposed. The stepwise regression is applied to extract the feature from the satellite image of FY-2C. The Logistic regression model is applied to detect the cloud. The result of experiment, compared with the surface observations, shows that the Logistic regression model is effective for cloud image processing, and the method is more accurate than the traditional threshold algorithm.

关 键 词：LOGISTIC回归 卫星云图 云检测 特征提取 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]