Algorithm of Minimizing Local Region Energy for Image Segmentation

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Algorithm of Minimizing Local Region Energy for Image Segmentation

更新时间：2025-07-09

- Algorithm of Minimizing Local Region Energy for Image Segmentation
- Vol. 45, Issue 8, Pages: 7-12(2011)
- 作者机构：
  
  1. 西安交通大学电子与信息工程学院,西安,710049
  2. 西安建筑科技大学信息与控制工程学院,西安,710055
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 August 2011，
  
  Published：2011
- 稿件说明：
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Algorithm of Minimizing Local Region Energy for Image Segmentation[J]. 2011, 45(8): 7-12.
DOI：

Algorithm of Minimizing Local Region Energy for Image Segmentation[J]. 2011, 45(8): 7-12. DOI：

摘要

针对点对马尔可夫随机场(Pairwise MRF)模型中像素成对交互的结构不能充分描述图像丰富的局部统计特征问题

在研究Pairwise MRF模型基础上

提出了一种基于局部区域能量最小化的图像分割算法. 该算法先利用图像局部区域信息构造局部区域能量模型

建立了一种局部交互的区域马尔可夫随机场分割模型

然后采用无环置信传播(LBP)算法对MRF全局能量进行优化.优化过程中

对局部区域能量进行收敛并按照MAP准则估计局部区域标号

通过LBP算法把局部区域信息传递到邻域区域中去.实验结果表明

所提出的新算法较标准LBP算法具有更好的分割结果

并有效地抑制了图像噪声信号和纹理信号对分割结果的干扰和影响.

Abstract

An algorithm of minimizing local region energy is proposed based on pairwise Markov random fields(MRF)model to solve the problem that the pairwise interactions fails to capture the rich statistical features of images. The proposed algorithm utilizes local region information to construct a local region energy model and a local interaction region MRF model for image segmentation. The loopy belief propagation(LBP)algorithm is applied to minimize the MRF global energy. The optimization makes local region energy converge

and the label is estimated based on MAP criterion. Then the local region information is transferred to adjacent region through LBP algorithm. Experimental results show that the proposed algorithm generates more accurate segmentation results than the standard LBP algorithm does on both synthetic and natural images

and also can efficiently restrain effect of image noise and texture for segmentation.

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Keywords

references

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