Methods: Based on Markov random fields model of noise, a iteration algorithm was presented by using maximum a posteriori (MAP) criterion.
方法：根据马尔科夫随机场图像模型，利用最大后验概率准则(MA P)，提出一种迭代松弛分割算法。
Conditional Random Fields (CRF) is arbitrary undirected graphical model that bring together the best of generative models and Maximum Entropy Markov models (MEMM).
条件随机场是一种无向图模型，它具有产生式模型和最大熵马尔可夫模型的优点。
Due to the problems to infrared image segmentation using Markov random fields, a method for infrared image segmentation based on triplet Markov fields using mixture gauss model was proposed.
针对马尔可夫随机场在红外图像分割方面存在的问题，给出了一种基于混合高斯模型的三马尔可夫场红外图像分割算法。
Triplet Markov random fields (TMF) model is suitable for dealing with multi-class segmentation of non-stationary, non-Gaussian SAR images.
三重马尔科夫随机场(TMF)模型非常适合处理非平稳、非高斯图像的分割问题。
Triplet Markov random fields (TMF) model is suitable for dealing with multi-class segmentation of non-stationary, non-Gaussian SAR images.
三重马尔科夫随机场(TMF)模型非常适合处理非平稳、非高斯图像的分割问题。
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