LIU Shuo, WU Honggan, WEN Qingke. Segmentation of Remote Sensing Image Based on a Combination of Genetic Algorithm and Ant Colony Algorithm[J]. Geomatics and Information Science of Wuhan University, 2009, 34(6): 679-683.
Citation: LIU Shuo, WU Honggan, WEN Qingke. Segmentation of Remote Sensing Image Based on a Combination of Genetic Algorithm and Ant Colony Algorithm[J]. Geomatics and Information Science of Wuhan University, 2009, 34(6): 679-683.

Segmentation of Remote Sensing Image Based on a Combination of Genetic Algorithm and Ant Colony Algorithm

  • We combine genetic algorithm(GA) with ant colony algorithm(ACA),which is introduced to optimize fuzzy cluster.Both pixel features and spatial features are extracted subtly,which are all used as cluster basis in intelligent computation.Niche genetic algorithm is used to optimize the course of looking for multiple optimal cluster centers.ACA is used to optimize the course of fuzzy clusters.In this way,the accuracy of image segmentation is improved greatly,and the course of image segmentation is accelerated as well.Experimental results show that the method proposed this paper is an efficient approach to segmentation of remote sensing image.
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