Adaptive Multi-scale Segmentation of High Resolution Remote Sensing Images Based on Particle Swarm Optimization

Multi-scale segmentation method is suitable for segmenting high resolution remote sensing images, however, it is difficult to get optimal multi-scale segmentation parameters using traditional methods. Particle swarm optimization (PSO) is a new evolutionary computing technique Based on swarm intelligence of bird flocks. Due to its intelligent properties, PSO is applied in selection of image multi-scale segmentation parameters adaptively in this paper. The particles in the swarm are constructed and the swarm search strategy is proposed to meet the needs of multi-scale segmentation parameter selection. The experimental results show that the PSO method is an effective parameter selection method and multi-scale segmentation Based on PSO can obtain satisfactory image segmentation results.