Gray-Level Image Segmentation Based on Markov Chain Monte Carlo

机译：基于马尔可夫链蒙特卡罗的灰度图像分割

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A new method called Markov chain Monte Carlo (MCMC) is proposed for image segmentation. The MCMC method mainly contains three aspects. Firstly, the image segmentation problem is formulated in a Bayesian statistical framework. Four types of gray-level image models are set up. Secondly, the solution space is decomposed into a union of many subspaces. Thirdly, ergodic Markov chains are designed to explore the solution space and sample the posterior probability. We test the MCMC algorithm on a wide variety of gray-level images and some results are shown in the paper.

机译：提出了一种称为马尔可夫链蒙特卡罗（MCMC）的图像分割方法。 MCMC方法主要包含三个方面。首先，在贝叶斯统计框架中提出了图像分割问题。建立了四种类型的灰度图像模型。其次，解空间被分解成许多子空间的并集。第三，设计遍历马尔可夫链来探索解空间并采样后验概率。我们在各种灰度图像上测试了MCMC算法，并在本文中显示了一些结果。

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《Education Technology and Computer Science, 2009. ETCS '09》|2009年|p.279-282|共4页
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Wenqing Huang; Kebiao Zheng; Xiaokai Zhu;
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中图分类计算技术、计算机技术;
关键词
Bayes methods; Markov processes; Monte Carlo methods; image segmentation; probability; Bayesian statistical framework; Markov chain Monte Carlo; gray-level image segmentation; posterior probability; Markov Chain Monte Carlo(MCMC); gray-level image;

机译：贝叶斯方法;马尔可夫过程;蒙特卡洛方法;图像分割;概率;贝叶斯统计框架;马尔可夫链蒙特卡洛;灰度图像分割;后验概率;马尔可夫链蒙特卡洛（MCMC）;灰度图像;

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2. Parts-based Segmentation With Overlapping Part Models Using Markov Chain Monte Carlo [J] . Matthias Seise, Stephen J. McKenna, Ian W. Ricketts, Image and Vision Computing . 2009,第5期

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3. REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO METHODS AND SEGMENTATION ALGORITHMS IN HIDDEN MARKOV MODELS [J] . R. Paroli, rnL. Spezia Australian & New Zealand journal of statistics . 2010,第2期

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4. Gray-Level Image Segmentation Based on Markov Chain Monte Carlo [C] . Wenqing Huang, Kebiao Zheng, Xiaokai Zhu International Workshop on Education Technology and Computer Science;ETCS 2009 . 2009

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Gray-Level Image Segmentation Based on Markov Chain Monte Carlo

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