基于萤火虫优化算法的红外图像增强研究

Infrared image enhancement based on firefly algorithm

为了提高红外图像增强的质量,采用萤火虫优化算法。首先对红外热区进行标示,通过直线函数对目标与背景阈值快速确定;然后结合人眼最小灰度分辨力函数对图像进行高斯混合建模进行红外图像细节增强;接着萤火虫优化算法在其动态决策域半径进行数据更新,对模型求解。实验仿真结果显示,该算法能够增强红外图像的细节信息,检测指标EME、PC、UIQI数据较优。

In order to improve the quality of infrared image enhancement, a firefly algorithm is proposed.Firstly, infrared hot zone is marked, and linear function of target and background threshold quickly is determined.Secondly, Gaussian mixture modeling for infrared image detail enhancement are established by human minimum gray level resolution force function. Then, firefly optimization algorithm is updated the data in the dynamic decision domain semi diameter, which is solved in the model.Simulation results show that firefly algorithm can enhance the detail information of the infrared image, detection index EME,PC, UIQI data is better.