Multi-Threshold Image Segmentation Based on Enhanced Arithmetic Optimization Algorithm
In view of the issues of poor segmentation quality and slow segmentation speed in traditional multi-threshold image segmentation methods,a multi-threshold image segmentation method based on enhanced arithmetic optimization algorithm is proposed.Double reverse learning is used to initialize the population,enhance the search performance of the algorithm.The spi-ral search strategy of tuna swarm optimization algorithm is introduced into the addition and subtraction strategy of arithmetic op-timization algorithm to enhance the ability of jumping out of local optimization.An adaptive cosine acceleration function is pro-posed to better balance the development and exploration ability of the algorithm.The experimental results show that the method proposed is able to segment better quality images while improving the convergence efficiency of the algorithm.
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