Unsupervised SAR Image Segmentation Based on Triplet Markov Fields With Graph Cuts

Gan L.; Wu Y.; Wang F.; Zhang P.

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Unsupervised SAR Image Segmentation Based on Triplet Markov Fields With Graph Cuts

机译：基于图割的三重马尔可夫场的无监督SAR图像分割

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摘要

The triplet Markov fields (TMF) model is suitable for dealing with nonstationary synthetic aperture radar (SAR) images. Existing optimization approaches for the TMF model cannot balance segmentation accuracy and computational efficiency. Focusing on efficient optimization of the TMF model, we propose an unsupervised SAR image segmentation algorithm based on TMF with graph cuts (GCs) in this letter. Considering the existence of two label fields in the TMF model, an iterative optimization strategy under the criterion of maximum a posteriori is proposed, which iteratively estimates one label field with the other fixed. GCs are is used to find the optimal estimation of each label field. GCs optimization and parameter estimation using iterative conditional estimation perform iteratively, leading to an unsupervised segmentation algorithm. Experiments on simulated and real SAR images demonstrate that the proposed algorithm can obtain accurate segmentation results with reasonable computational cost.

机译：三重态马尔可夫场（TMF）模型适用于处理非平稳合成孔径雷达（SAR）图像。 TMF模型的现有优化方法无法平衡分割精度和计算效率。着眼于TMF模型的有效优化，在本文中，我们提出了一种基于TMF的无监督SAR图像分割算法。考虑到TMF模型中存在两个标签字段，提出了一种在最大后验准则下的迭代优化策略，该迭代优化策略迭代估计一个标签字段，而另一个固定。 GC用于查找每个标签字段的最佳估计。使用迭代条件估计的GC优化和参数估计会迭代执行，从而导致无监督的分割算法。在模拟和真实SAR图像上的实验表明，该算法能够以合理的计算量获得准确的分割结果。

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《IEEE Geoscience and Remote Sensing Letters》 |2014年第4期|853-857|共5页
作者
Gan L.; Wu Y.; Wang F.; Zhang P.;
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Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an, China|c|;

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正文语种 eng
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关键词
Graph cuts (GCs); nonstationary property; synthetic aperture radar (SAR) image segmentation; triplet Markov fields (TMF);

机译：图割（GCs）;非平稳性;合成孔径雷达（SAR）图像分割;三重马尔可夫场（TMF）;

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专利

1. Unsupervised multi-class segmentation of SAR images using triplet Markov fields models based on edge penalty [J] . Yan Wu, Ming Li, Peng Zhang, Pattern recognition letters . 2011,第11期

机译：基于边缘罚分的三重态马尔可夫场模型对SAR图像进行无监督的多类分割
2. Unsupervised SAR Image Segmentation Based on Conditional Triplet Markov Fields [J] . IEEE Geoscience and Remote Sensing Letters . 2014,第7期

机译：基于条件三重态马尔可夫场的无监督SAR图像分割
3. Unsupervised multi-class segmentation of SAR images using fuzzy triplet Markov fields model [J] . Zhang P., Li M., Wu Y., Pattern Recognition: The Journal of the Pattern Recognition Society . 2012,第11期

机译：模糊三重态马尔可夫场模型的无监督SAR图像多类分割
4. Unsupervised segmentation of SAR images using Triplet Markov fields and fisher noise distributions [C] . Benboudjema Dalila, Tupin Florence, Pieczynski Wojciech, IEEE International Geoscience and Remote Sensing Symposium . 2007

机译：使用Triplet Markov领域和Fisher噪声分布的SAR图像无监督分割
5. Unsupervised segmentation of noisy and textured images modeled by Markov random fields. [D] . Gregoriou, Georghios Kyriacos. 1992

机译：由Markov随机场建模的噪点和纹理图像的无监督分割。
6. Unsupervised Cerebrovascular Segmentation of TOF-MRA Images Based on Deep Neural Network and Hidden Markov Random Field Model [O] . Shengyu Fan, Yueyan Bian, Hao Chen, 2019

机译：基于深度神经网络和隐马尔可夫随机场模型的TOF-MRA图像无监督脑血管分割
7. Unsupervised segmentation of SAR images using Triplet Markov fields and Fisher noise distributions [O] . Dalila Benboudjema, Florence Tupin, Wojciech Pieczynski, 2012

机译：利用三重马尔可夫场和Fisher噪声分布对saR图像进行无监督分割
8. Graph-cut Based Interactive Segmentation of 3D Materials-Science Images [R] . Waggoner, J, Zhou, Y, Simmons, J, 2014

机译：基于图形切割的三维材料 - 科学图像交互式分割

Unsupervised SAR Image Segmentation Based on Triplet Markov Fields With Graph Cuts

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