摘要
传统的医学图像增强算法存在适用性差、计算量大和参数人工设置等缺点。本文结合果蝇优化算法的良好的全局最优搜索性能,针对FOA算法存在局部最优问题,将改进因子引入FOA算法,提出一种IFOA优化模糊熵的自适应医学图像增强算法。实验结果表明,IFOA算法可以有效地突出图像的特征,改善图像的视觉效果,提高效率,避免手工调整参数的不便,在保证图像质量最佳的情况下,可以自动配置出最佳的模糊增强参数,实现医学图像的自适应增强。
For there are poor application, a great number of calculations and the artificial parameter settings in the traditional medical image enhancement algorithm, this paper took advantage of the good global optimal search performance and local optimum in FOA to introduce improved factors into it to propose an optimized IFOA adaptive fuzzy entropy image enhancement algorithm. The results showed that the IFOA algorithm could effectively underline the image characteristics,improvement of visual effect and efficiency of images to avoid the manual adjustment of parameters in favor of automatic configuration for the optimal parameters of fuzzy enhancement in order to achieve the adaptive enhancement of medical image.
作者
陈智勇
CHEN Zhi-yong(Qinghai Normal University, Xining 810000, China)
出处
《山东农业大学学报（自然科学版）》
CSCD
2017年第1期104-107,共4页
Journal of Shandong Agricultural University：Natural Science Edition
关键词
果蝇优化算法
自适应
图像处理
Fruit Fly Optimization Algorithm
adaptive enhancement
image process
