林达, 徐新, 潘雪峰, 张海涛. 一种新的MSTAR SAR图像分割方法[J]. 武汉大学学报 ( 信息科学版), 2014, 39(11): 1314-1317.
引用本文: 林达, 徐新, 潘雪峰, 张海涛. 一种新的MSTAR SAR图像分割方法[J]. 武汉大学学报 ( 信息科学版), 2014, 39(11): 1314-1317.
shu
Lin Da, Xu Xin, Pan Xuefeng, Zhang Haitao. Segmentation of SAR Image of MSTAR SAR Chips Based on Attributed Scattering Center Feature and Markov Random Field[J]. Geomatics and Information Science of Wuhan University, 2014, 39(11): 1314-1317.
Citation: Lin Da, Xu Xin, Pan Xuefeng, Zhang Haitao. Segmentation of SAR Image of MSTAR SAR Chips Based on Attributed Scattering Center Feature and Markov Random Field[J]. Geomatics and Information Science of Wuhan University, 2014, 39(11): 1314-1317.
shu

一种新的MSTAR SAR图像分割方法

Segmentation of SAR Image of MSTAR SAR Chips Based on Attributed Scattering Center Feature and Markov Random Field

    摘要
  • 摘要: 提出了一种新的MSTAR SAR图像分割方法。该方法首先根据地物的散射机制进行属性散射中心(attributed scattering centers,ASC)特征提取，构造属性散射中心特征向量;然后使用马尔科夫随机场(Mark-ov random ficld,MRF)结合属性散射中心特征对MS"IAR SAR图像进行空间邻域关系描述;最后运用标号代价能量优化算法得到最终的分割结果。MS"IAR SAR数据上的实验结果证明了其有效性。

     

    Abstract: A novel segmentation method is proposed for MSTAR SAR target chips. First，feature extraction is implemented to acquire the attributed scattering center(ASC) feature vectors based on scattering characteristics. Then， a Markov random field(MRF) with the attributed scattering center feature is used to describ the spatial contextual information of different segments in the SAR image ofMSTAR SAR chips. The final segmentation result is obtained by combining an optimized algorithm oflabel costs. Experimental results validate the effectiveness of this improved algorithm.

     

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