一种采用改进细菌觅食优化算法的图像增强方法

为了解决现有图像增强技术在细节处理方面的不足以及变换后图像直方图分布偏移的情况，提出一种采用改进细菌觅食优化算法的灰度图像增强方法。针对细菌觅食算法在优化高维函数时性能不佳、易陷入早熟收敛的缺陷，将变高维的灰度图像增强问题转化为固定2维的非完全Beta函数的参数最优化问题。仿真实验结果表明了所提出方法的有效性，与其他方法相比，增强后的图像细节表现更自然，直方图分布更均匀，明暗区域分配更合理。

Image enhancement method based on improved bacteria foraging optimization algorithm

A gray image enhancement method is proposed based on an improved bacterial foraging optimization algorithm, so that the problems of the insufficient detail processed by the traditional image enhancement technology and the offset of histogram distribution after the transformation are solved. To avoid becoming prone to fall into the defects of premature convergence and other poor performances in swarm intelligence algorithms when optimizing high dimensional functions, a gray-scale image enhancement problem whose dimensions are high and variational is converted into a fixed two-dimensional parameters optimization problem of the incomplete Beta function. Simulation results show the effectiveness of the proposed method. Comparing with other methods, enhanced image makes the details more natural, the histogram distribution more uniform, and the light and dark areas more reasonable.