Fuzzy clustering is an important method in unsupervised classification.In application of traditional fuzzy clustering algorithm to unsupervised classification of remote sensing imagery

pixels are assumed to be independent of each other and their fuzzy memberships are determined individually

so that context information

i.e.statistical dependencies among neighboring pixels

are not taken into account.Aiming at this problem

an improved fuzzy clustering algorithm considering context information is put forward by incorporating the concept of spatial fuzzy membership under MRF framework.In this way

accuracy and reliability of clustering can be improved upon traditional ones.To evaluate the quality of clustering results

a validation index considering both intra-cluster compactness and inter-cluster separation is introduced

further more it is employed to find out naturally optimal cluster numbers and promote objectivity of clustering results.Finally an experiment on real remote sensing imagery is carried out to demonstrate the effectiveness of our proposed scheme.