The Ant System Applied to the Quadratic Assignment Problem
IEEE Transactions on Knowledge and Data Engineering
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Remote sensing images classification method can be divided into supervised classification and unsupervised classification according to whether there is prior knowledge. Supervised classification is a machine learning procedure for deducing a function from training data; unsupervised classification is a kind of classification which no training sample is available and subdivision of the feature space is achieved by identifying natural groupings present in the images values. As a branch of swarm intelligence, ant colony optimization algorithm has self-organization, adaptation, positive feedback and other intelligent advantages. In this paper, ant colony optimization algorithm is tentatively introduced into unsupervised classification of remote sensing images. A series of experiments are performed with remote sensing data. Comparing with the K-mean and the ISODATA clustering algorithm, the experiment result proves that artificial ant colony optimization algorithm provides a more effective approach to remote sensing images classification.