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Remote Sensing Image Change Detection Based on Swarm Intelligent Algorithm

For several decades the remote sensing change detection methods for depicting land cover have gained a great achievements, and the artificial intelligence techniques have being applied to remote sensing data processing and show great potential. Ant colony optimization (ACO) and Particle swarm optimization (PSO) as the two main algorithms of swarm intelligence, and because of the self-organization, cooperation, communication and other intelligent merits, they have great potential in research area. This paper introduces remotely sensed image change detection using the swarm intelligent algorithm. Selecting Landsat-5 TM image located in Beijing area as experimental data, this paper use the algorithm for constructing the change rules, then use these rules to process the example data, the experiment results show that warm intelligent algorithm has provided a new method for remote sensing image change detection.