MARKOV RANDOM FIELD TEXTURE MODELS
MARKOV RANDOM FIELD TEXTURE MODELS
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DOI：
10.1109/tpami.1983.4767341
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发表时间：
1983-01-01
影响因子：
23.6
通讯作者：
JAIN, AK
中科院分区：
文献类型：
--
作者：
CROSS, GR;JAIN, AK
我们认为纹理是一个随机的、可能是周期性的二维图像场。纹理模型是能够生成和描述纹理图像的数学过程。我们探索使用马尔可夫随机场作为纹理模型。二项式模型被视为分析的基本模型，其中纹理中的每个点都具有二项式分布，参数由其邻居控制，“尝试次数”等于灰度级数。给出了一种从二项式模型生成样本的方法，并对该方法的收敛性进行了理论和实践分析。示例显示了马尔可夫随机场的参数如何控制图像中聚类的强度和方向。展示了二项式模型产生模糊、锐利、线状和斑点状纹理的能力。将自然纹理样本数字化，并在马尔可夫随机场模型下估计其参数。假设检验用于在马尔可夫随机场模型下客观评估拟合优度。总体而言，微观纹理非常适合模型。自然纹理的估计参数用作生成过程的输入。合成的微观纹理与真实的纹理非常相似，而规则和不均匀的纹理则不然。
We consider a texture to be a stochastic, possibly periodic, two-dimensional image field. A texture model is a mathematical procedure capable of producing and describing a textured image. We explore the use of Markov random fields as texture models. The binomial model, where each point in the texture has a binomial distribution with parameter controlled by its neighbors and ``number of tries'' equal to the number of gray levels, was taken to be the basic model for the analysis. A method of generating samples from the binomial model is given, followed by a theoretical and practical analysis of the method's convergence. Examples show how the parameters of the Markov random field control the strength and direction of the clustering in the image. The power of the binomial model to produce blurry, sharp, line-like, and blob-like textures is demonstrated. Natural texture samples were digitized and their parameters were estimated under the Markov random field model. A hypothesis test was used for an objective assessment of goodness-of-fit under the Markov random field model. Overall, microtextures fit the model well. The estimated parameters of the natural textures were used as input to the generation procedure. The synthetic microtextures closely resembled their real counterparts, while the regular and inhomogeneous textures did not.