基于选权迭代估计与非监督分类的多光谱图像变化检测  

Change detection of multi-spectral images based on iterative estimation with weight selection and unsupervised classification

作　　者：李莎[1] 倪维平[1] 严卫东[1] 吴俊政[1] 张晗[1] 

机构地区：[1]西北核技术研究所,西安710024

出　　处：《国土资源遥感》2014年第4期34-40,共7页Remote Sensing for Land & Resources

摘　　要：针对多光谱图像的变化检测问题,提出了一种基于选权迭代估计(iterative estimation with weight selection,IEWS)与非监督分类(unsupervised classification,UC)的多光谱图像变化检测方法。借鉴IEWS的思想,并以类似于迭代加权多元变化检测(iteratively reweighted multivariate alteration detection,IRMAD)的迭代模式进行回归估计,得到初步的变化检测结果;并通过对初始变化信息的UC处理,以及对不同类别的IEWS,得到最终的变化检测结果。利用该方法对TM图像进行了实验,结果表明:所得到的变化信息在空间位置上同该区域相应时间段内土地利用/覆盖的变化情况具有很好的一致性;同时与多元变化检测及IRMAD方法变化检测的结果相比较,表明该方法对相对较小的变化信息具有更好的变化检测能力。To solve the change detection problem of multi-channel remote sensing images, this paper proposes a method based on iterative estimation with weight selection （ IEWS） and unsupervised classification （ UC） . Firstly, the primary change information is obtained according to the concept of IEWS, and the iteration scheme of the estimation is also similar to that of the iteratively re -weighted multivariate alteration detection （ IRMAD ） . And then, the primary change information is classified by the UC and processed by the IEWS, which can get the eventual change information. The experimental results with multi-spectral data indicate that the method proposed in this paper is effective. By using this method, the spatial coherence between the change information and the change of land use/cover in this area is good. As for the detection of change in small regions, the method is especially obviouely better than the commonly-used methods of multivariate alteration detection （ MAD） and IR-MAD.

关 键 词：多光谱图像 变化检测 选权迭代估计(IEWS) 迭代加权多元变化检测(IRMAD) 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]