基于改进同态滤波的红外图像增强算法

Infrared Image Enhancement Algorithm Based on Improved Homomorphic Filtering

针对红外图像的边缘细节特征不清晰、整体对比度低等问题,提出一种结合单参数同态滤波和限制对比度的自适应直方图均衡的红外图像增强算法。首先,基于单参数的同态滤波对图像进行处理,研究一种单一参数的传递函数,使得同态滤波算法参数可控且不依赖于实验经验,同时明显增强红外图像的细节特征。然后,利用限制对比度的自适应直方图均衡化对红外图像进行动态范围调整,提高红外图像对比度。实验仿真结果表明,该算法可以明显增强图像细节特征、提高图像对比度,使红外图像更有利于后续观察。

To solve the problems of unclear edge details and low overall contrast of infrared images,an adaptive histogram equalization algorithm combining single parameter homomorphic filtering and limited contrast is proposed.First,the image is processed based on homomorphic filtering with single parameter,and a transfer function with single parameter is studied to make the homomorphic filtering algorithm parameters controllable and independent of experimental experience,while significantly enhancing the details of infrared images.Then,the adaptive histogram equalization with limited contrast is used to adjust the dynamic range of the infrared image to improve the contrast of the infrared image.The simulation results show that the algorithm can significantly enhance the image details,improve the image contrast,and make the infrared image more conducive to subsequent observation.