【摘要】 针对全极化SAR影像的特点以及传统分割方法存在的问题,提出了一种综合多特征(多种极化特征和形状特征)的全极化SAR建筑物分割模型。该模型采用分形网络演化算法及多元线性回归模型,构建综合多特征的建筑物分割模型。实验结果表明,该模型能够显著提高分割的精度,并且分割对象个数比较合理。更多还原

【Abstract】 The existing segmentation methods mostly directly use backscatter coefficient images or span images for segmentation,or a certain kind of polarization characteristic images,and do not make full use of the polarimetric characteristics and spatial characteristics.We propose a buildings segmentation model based on PolSAR images,which makes full use of the polarimetric characteristics and spatial characteristics of buildings by FNEA(fractal network evolutionary algorithm) and MLR(multiple linear regression) model.Using the proposed model to achieve the segmentation of the L-band EMISAR airborne images in Foulum area.The experimental results show that the segmentation model is feasible.更多还原