基于改进蛙跳算法的图像自适应增强研究

Image Adaptive Enhancement Research Based on Improved Shuffled Frog Leap Algorithm

为了提高图像增强的效果，提出改进蛙跳算法。首先对蛙群分组，一组采用群体智能算法，另一组用自适应算法；基于实数算法对图像像素映射编码；然后通过模糊集合对蛙跳微调更新；最后以均方误差函数作为评价函数，通过Beta非线性变换函数最优参数值实现图像自适应增强。实验仿真结果得出：改进蛙跳算法对图像增强对比度较高，处理时间少，像素数据求解精度高。

To improve the effect of image enhancement, improved shuffled frog leaping algorithm was proposed. Firstly, frogs were grouped, one was used swarm intelligence algorithm, and another was used adaptive algorithm. Secondly, image pixel was mapped code based on real encoding. Thirdly, leap frog was Trimmed update based on fuzzy set. Finally, mean square error function was as evaluation function, and image adaptive enhancement was achieved based on Beta nonlinear transformation function optimal parameter value. Experimental simulation result show： improved shuffled frog leap algorithm has high contrast for image enhancement, processing time is less, pixel data obtained has high orecision.