摘要
为提高图像增强的自适应性,首先将细菌的自适应趋向因子引入到细菌觅食算法中,然后将提升的细菌觅食算法和非完全Beta函数结合而去获得最佳的灰度变换参数,最终实现对降质图像的最大程度的自适应增强。仿真实验结果表明,提升的优化算法可以更好的优化Beta函数的参数,因而能更有效地提高图像整体对比度和视觉效果。
To improve the adaptive performance of image enhancement, firstly, a kind of adaptive chemotaxis factor of bacteria is employed to the bacterial foraging optimization. Then the improved adaptive bacterial foraging algorithm （ABFA） is combined with the incomplete Beta function to obtain the optimum grey translation parameters. Finally, the degraded image is enhanced adaptively to the utmost extent. The simulation results show that the improved optimization algorithm is more efficient to refine parameters of the Beta function than its counterpart, which enhances the global contrast of the image and visual effect.
出处
《河北工程大学学报（自然科学版）》
CAS
2013年第1期77-81,共5页
Journal of Hebei University of Engineering:Natural Science Edition
基金
河北省高等学校科学研究计划项目(项目编号:2011138)
关键词
细菌觅食算法
图像增强
优化算法
趋向因子
bacterial foraging algorithm
image enhancement
optimization algorithm
chemotaxis factor
