| 赵伟,田铮,杨丽娟,延伟东.基于局部平滑加权图割方法的SAR图像分割[J].光电子激光,2014,(11):2212~2218 |
| 基于局部平滑加权图割方法的SAR图像分割 |
| SAR image segmentation using local smoothing weighted graph cut |
| 投稿时间：2014-03-16 |
| DOI： |
| 中文关键词: 图像处理 合成孔径雷达(SAR)图像分割 图割 加权核K均值(WKKM ) |
| 英文关键词:image processing synthetic aperture radar (SAR) image segmentation graph cut weighted kernel K-means (WKKM) |
| 基金项目:国家自然科学基金(60972150、61201323、61301196)、陕西省自然科学基础研究计划(2014JQ5189)和遥感科学国家重点实验室开放基金(OFSLRSS201206)资助项目 (1.西北工业大学 应用数学系,陕西 西安 710072； 2.中国科学院遥感科学国家重点实验室,北京 100101) |
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| 中文摘要: |
| 针对合成孔径雷达(SAR)图像分割,提出了一种 局部平滑加权图割(LSWGC,local smoothing weighted graph cut)模型。首先,在加权图割(WGCut)的目标函数中加入局部平滑罚项,提高了基于谱 聚类的SAR 图像分割方法对斑点噪声的稳健性,抑制了SAR图像分割中孤立点的产生；其次,利用WGCut 与加权核 K均值(WKKM)的等价性,LSWGC以不同于参数核 图割(PKGC)方法的核化方式将核映射引入目标函数中,用图 割最优化算法求解标号函数,避免了基于谱聚类的SAR图像分割方法中图谱的求解问题,同 时改善了PKGC方法二类划分易丢失目标的不足。模拟和真实SAR图像的实验结果证实 了本文方案的有效性。 |
| 英文摘要: |
| The segmentation of synthetic aperture radar (SAR) images is a challenging task. The difficulty lies in that the existence of speckle noise leads to the segmentation of small sets of isolated pixels.To solve this problem,a local smoothing weighted graph cut model is pre sented in this paper. Firstly,a smoothness regularization term is introduced into the weighted graph cut model.As a result,the robustness of the spectral clustering based SAR image segmentation methods to sp eckle noise is improved and small sets of isolated pixels are restrained.Secondly,using the e quivalence relation between the weighted graph cut model and weighted kernel K-means,kernel mappin g is added to the objective function of local smoothing weighted graph cut model with a different fashion from parametric kernel graph cuts,and the label function can be solved via graph cut optimizatio n algorithm.The method avoids calculating graph spectrum,which is a key step of spectral clustering ba sed SAR image segmentation methods.Meanwhile,it makes up for the deficiency of parametric ke rnel graph cuts method when the segmentation number is two.Experimental results with simulated a nd real-world SAR images demonstrate that the proposed method is effective and provides comparable or bet ter results than the classical graph cut based methods. |
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