一种快速有效的MSTAR SAR目标图像分割算法

基金项目: 国家863计划资助项目(2007AA12Z155)；湖北省自然科学基金资助项目(2007ABA257)

详细信息

A Fast and Effective Segmentation Algorithm for MSTAR SAR Target Chips

¹ School of Electronic Information,Wuhan University,129 Luoyu Road,Wuhan 430079,China

Funds: 国家863计划资助项目(2007AA12Z155)；湖北省自然科学基金资助项目(2007ABA257)

摘要: 提出了一种快速有效的SAR目标图像分割算法。该算法基于混合Gamma分布,利用改进的Potts模型引入先验信息,通过结合期望最大化和图切割优化算法(GC)对混合分布模型参数进行快速稳健的估计,从而获得最终的分割结果。在MSTAR SAR数据集上的实验表明了该算法的有效性和灵活性。
- 图像分割 /
- 有限混合模型 /
- 期望最大化 /
- 图切割
Abstract: We present a fast and effective segmentation algorithm for MSTAR SAR target chips.The algorithm is based on finite mixture models,by which the segmentation is posed as an inference problem through introducing an improved potts model base on MRF.The final segmentation result is obtained by fast and robust parameters estimation based on combining expectation maximization and graph cut optimization.We compare its performance to conventional MRF methods based on three standard image segmentation indices using MSTAR SAR data sets,and experimental results show that our proposed algorithm has better performance than traditional MRF method.
- image segmentation /
- finite mixture model /
- expectation maximization /
- graph cut