一种新的MSTAR SAR图像分割方法

基金项目: 国家973计划资助项目2013CB733404

详细信息

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

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"I}AR 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"I}AR SAR数据上的实验结果证明了其有效性。
- MSTAR SAR图像分割 /
- 属性散射中心特征提取 /
- 马尔科夫随机场 /
- 能量优化
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.
- MSTAR SAR image segmentation /
- feature extraction of attributed scattering center /
- Markov random field(MRF) /
- energy optimization