%0 Journal Article
%T 融合SRADPRO和SCM模型的SAR图像分割
%A 寇光杰
%A 马云艳
%A 岳峻
%J 北京邮电大学学报
%D 2016
%R 10.13190/j.jbupt.2016.01.023
%X 摘要 将改进后各向异性扩散相干斑抑制算法(SRADPRO)用于合成孔径雷达(SAR)图像相干斑抑制,并和脉冲发放皮层模型(SCM)结合,提出一种自适应SAR图像分割算法.该算法首先计算SAR图像均匀采样区的标准差,并以此评价SAR图像中相干斑的影响程度,进而自适应地决定是否采用SRADPRO进行降斑处理,然后再利用SCM进行图像分割.由于SCM的自动波扩散机理,使得该算法在获得分割后的SAR目标的同时,也得到了目标边缘检测结果.与多种常规算法的比较结果证明了SAR图像分割算法的有效性.</br>An improved speckle reducing anisotropic diffusion (SRADPRO) algorithm was adopted to reduce the speckle in synthetic aperture radar (SAR) image. An adaptive SAR image segmentation algorithm speckle reducing spiking cortical model (SRSCM) was proposed when SRADPRO and spiking cortical model (SCM) was combined. In SRSCM, the standard deviation was calculated through a uniform sample region in the SAR image, and then the effect degree of speckle can be estimated as a result whether to employ the operator of SRADPRO was determined. At the second stage, the SCM operator was executed. Because of the auto wave characteristic of SCM, the segmented image and edge detection result can be obtained together. The effectiveness of SRSCM was proved by the comparisons with several traditional algorithms.
%K 各向异性扩散
%K 脉冲发放皮层模型
%K 合成孔径雷达图像分割
%K 边缘检测
%K 相干斑&lt
%K /br&gt
%K Key words： anisotropic diffusion spiking cortical model synthetic aperture radar image segmentation edge detection speckle
%U http://journal.bupt.edu.cn/CN/abstract/abstract2837.shtml