An ant colony optimization approach for SAR image segmentation

A novel SAR image segmentation algorithm, based on the Ant Colony Optimization (ACO) method is proposed in this paper. The method extended the ant colony algorithm to threshold optimization, two-dimension fuzzy entropy is used as objective function, and ant move direction is determined by the trail pheromone. Each ant in the colony will generate a path based on the relative positions of the nodes and feedback information about the best paths generated by previous colonies. The solution of each ant is improved by using a global optimization procedure. The proposed approach has been tested on different SAR images. Tests results show that, due to its ability of both finding good search paths and escaping from local minima, the proposed method could achieve a near-optimal solution to the SAR image segmentation problem.