Abstract：The characteristics of data can not be simulated in the traditional fuzzy clustering method effectively. Gaussian mixture model with neighbor constraints is introduced to solve the problem. Gaussian distribution is used to characterize the statistical characteristics of spectral measure. The correlation between the pixels and their neighborhood pixels are defined as prior probability and used as weight coefficients of each component in Gaussian mixture model. Finally, a Gaussian mixture model with neighborhood constraints in feature field is constructed. Log weighted Gaussian component in the mixture model is used as dissimilar measurement between the pixels and clusters, and a fuzzy clustering objective function is constructed based on Gaussian mixture model. Neighborhood constraints are introduced as a weight of component in traditional Gaussian mixture model and combined with fuzzy clustering method. Thus, the problem of multi-peak distribution of data is solved. Finally, the accuracy of the proposed algorithm is verified by experiments.
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2017, Vol. 30 
