马尔科夫随机场MRF线性可变权重图像分割方法Markov Random FieldLiner Variable Weight Image Segmentation Method
李慧,张荣国,胡静,刘小君
摘要(Abstract)：
在对图像进行分割时,传统MRF模型没有考虑到像素间的相互关系,这样会使得分割不够准确。为此,本文提出了一种MRF线性可变权重图像分割方法。它在标记场和特征场中加入了邻域像素间的强度信息,从而可以有效运用图像空间信息。然后将指数型可变权重参数改为线性可变权重参数,来连接标记场和特征场,加快了分割结果更新速度,增大了势函数的选择范围。实验显示,当用改进算法分割不同类型的图像时,本文提出的算法在分割结果的准确性和区域一致性上,更具有效性和鲁棒性。不管是在分割速度上还是图像处理效率上,都有了很大的提升。
关键词(KeyWords)： 图像分割;MRF;权重参数;线性可变权重
基金项目(Foundation): 国家自然科学基金(51375132);; 山西省自然科学基金(201801D121134);; 晋城市科技局资助项目(201501004-5)
作者(Author): 李慧,张荣国,胡静,刘小君
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