亮, 舒宁, 龚龑, 王凯. 一种面向像斑的高分辨率遥感影像相对辐射校正方法李[J]. 武汉大学学报 ( 信息科学版), 2014, 39(4): 401-405. DOI: 10.13203/j.whugis20120642
引用本文: 亮, 舒宁, 龚龑, 王凯. 一种面向像斑的高分辨率遥感影像相对辐射校正方法李[J]. 武汉大学学报 ( 信息科学版), 2014, 39(4): 401-405. DOI: 10.13203/j.whugis20120642
LI Liang, SHU Ning, GONG Yan, WANG Kai. An Object-oriented Relative Radiometric Normalization MethodUsing High Resolution Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2014, 39(4): 401-405. DOI: 10.13203/j.whugis20120642
Citation: LI Liang, SHU Ning, GONG Yan, WANG Kai. An Object-oriented Relative Radiometric Normalization MethodUsing High Resolution Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2014, 39(4): 401-405. DOI: 10.13203/j.whugis20120642

一种面向像斑的高分辨率遥感影像相对辐射校正方法李

An Object-oriented Relative Radiometric Normalization MethodUsing High Resolution Remote Sensing Images

  • 摘要: 目的 在认为不同类别地物的光谱响应值在不同时期具有不同的线性关系的基础上,提出了一种基于像斑的高分辨率遥感影像相对辐射校正方法。首先以相关系数为基础将像斑划分为变化像斑和未变化像斑两大类,再对未变化像斑利用随机数据一致性算法解求增益和偏移参数,对于变化像斑则将与其最相似的未变化像斑的增益和偏移参数作为该像斑的校正参数,最后利用各像斑的校正参数进行线性校正。在高分辨率遥感影像上的实验结果验证了本文方法的有效性。

     

    Abstract: Objective The assumption that the spectral responses of different types of objects in different periodshave the same linear relationship in traditional relative radiometric normalization is insufficient for theanalysis of high resolution remote sensing images.Object-oriented relative radiometric normalizationfor high resolution remote sensing image change detection is proposed in the paper based on the as-sumption that the spectral responses of different types of objects in different periods have different lin-ear relationships.Firstly,image objects are divided into two categories:changed and unchanged bycorrelation coefficients.Secondly,gains and offset parameters are calculated by an analysis of a ran-dom sampling consensus based on unchanged image objects.Thirdly,gains and offset parameters ofthe unchanged image objects which are most similar with the changed image objects are assigned to thechanged image objects.Lastly,the image objects are corrected using gain and offset parameters.Ex-periments on high resolution remote sensing images verify the effectiveness of the proposed method.

     

/

返回文章
返回