改进的狮群优化算法脑CT断层图像去噪研究

Improved Lion Swarm Optimization Algorithm for Image Denoising of Brain CT

目的为增强狮群优化算法对脑CT断层图像的去噪能力,提高算法寻找局部最优滤波器组合的效率,进而提升算法对脑CT断层图像的去噪效果。方法通过引入Tent映射,对狮群优化算法进行改进,利用Tent映射对狮群优化算法中所得的幼狮群体的局部最优组合进行混沌操作,通过加快混沌收敛的速度增强其局部寻优能力。结果改进的狮群优化算法对脑CT断层图像进行处理后,去噪图像在视觉效果与峰值信噪比方面均明显优于其他算法,改进的算法性能优良。结论改进后的算法收敛速度较快,可提升寻找最优滤波器组合的效率,并在保留脑CT图像视觉效果的同时显著提高去噪能力。

Objective To effectively enhance the denoising ability of the lion swarm optimization algorithm on brain CT images by improving the efficiency of the algorithm in finding the local optimal filter combination.Methods The lion swarm optimization algorithm was improved by introducing Tent mapping,which was used to carry out chaotic operation on the local optimal combination of the lion cubs,so as to enhance the local optimization ability of lion swarm optimization algorithm by accelerating the speed of chaotic convergence.Results The experimental results showed that the improved lion swarm optimization algorithm was significantly superior to other algorithms in terms of visual effect and peak signal to noise ratio after processing brain CT sectional images.The improved algorithm had excellent performance.Conclusion The improved algorithm effectively improves the efficiency of finding the optimal filter combination because of its faster convergence speed,and significantly improves the denoising ability while preserving the visual effect of brain CT images.