文章基本信息

标题：Unsupervised multispectral image Classification By fuzzy hidden Markov chains model For SPOTHRV Images
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作者：Mr. Faiza DAKKA ; Mr. Ahmed HAMMOUCH ; Mr. Driss ABOUTAJDINE 等
期刊名称：International Journal of Image Processing (IJIP)
电子版ISSN：1985-2304
出版年度：2011
卷号：5
期号：4
页码：446-455
出版社：Computer Science Journals
摘要：This paper deals with unsupervised classification of multi-spectral images, we propose to use a new vectorial fuzzy version of Hidden Markov Chains (HMC). The main characteristic of the proposed model is to allow the coexistence of crisp pixels (obtained with the uncertainty measure of the model) and fuzzy pixels (obtained with the fuzzy measure of the model) in the same image. Crisp and fuzzy multi-dimensional densities can then be estimated in the classification process, according to the assumption considered to model the statistical links between the layers of the multi-band image. The efficiency of the proposed method is illustrated with a Synthetic and real SPOTHRV images in the region of Rabat. The comparisons of two methods: fuzzy HMC and HMC are also provided. The classification results show the interest of the fuzzy HMC method.
关键词：Bayesian Image Classification; Markov Chains; Fuzzy Hidden Markov