Unsupervised multispectral image Classification By fuzzy hidden Markov chains model For SPOTHRV Images

This paper deals with unsupervised classification of multi-spectral images, we propose to usea 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 thefuzzy measure of the model) in the same image. Crisp and fuzzy multi-dimensional densitiescan then be estimated in the classification process, according to the assumption consideredto model the statistical links between the layers of the multi-band image. The efficiency of theproposed method is illustrated with a Synthetic and real SPOTHRV images in the region ofRabat.The comparisons of two methods: fuzzy HMC and HMC are also provided. The classificationresults show the interest of the fuzzy HMC method.