Image segmentation algorithm based on Markov random field(MRF) for radiography
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摘要: 目标界面位置信息是闪光照相中关注的内容之一，而闪光图像的低信噪比影响了微结构界面位置的准确提取。研究了基于马尔可夫随机场的闪光图像分割算法，在闪光图像分割过程中采用马尔可夫模型描述被分割像素之间的相关性，减少了由噪声所引起的孤立虚假目标，提出利用中空邻域模板内的起伏定义标号场模型中的基团势函数，改进了闪光图像的分割方法，提高了微结构分割精度。数值实验表明，改进后的马尔可夫随机场分割方法能取得更好的分割结果。Abstract: Boundary of different materials is one of the focus in flash X-ray radiography, low signal-to-noise ratio and microcosmic structure block the exact distilling of material boundary. In this paper, Markov random field method is researched, Markov model is used to describe the relativity between different pixels, to reduce the number of false target root in noise; through the variance of pixels in template with hollow center the energy cliques function is described, the segment result of microcosmic structure and segment precision of flash X-ray radiography are improved. Simulation shows the modified MRF method in this paper can get better segment result.
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Key words:
- image segmentation /
- flash X-ray radiography /
- Markov random field
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