基于大气灰度因子的红外图像增强算法  

Infrared image enhancement algorithm based on atmospheric gray factor

作　　者：王笛 沈涛 孙宾宾 崔晓荣 WANG Di;SHEN Tao;SUN Bin-bin;CUI Xiao-rong(Rocket Force University of Engineering,Xi'an 710025,China)

机构地区：[1]火箭军工程大学

出　　处：《激光与红外》2019年第9期1135-1140,共6页Laser & Infrared

基　　金：国家高技术研究发展计划项目(No.099018)资助

摘　　要：通过分析红外图像的成像特点,将图像的灰度空间来源分解为物体辐射以及大气辐射,并提出了大气灰度因子来表征由于大气辐射产生的灰度空间。为了改善图像质量,增强图像的视觉效果,通过建立基于大气灰度因子的灰度映射模型有效地消除了大气辐射造成的图像质量退化。针对增强图像出现的边缘比较粗糙的问题,本文以原始图像为引导,通过导向滤波对大气灰度因子进行修正。相较于传统的直方图均衡算法,本文的算法具有更强的适应性,能够在增强图像对比度的同时较好地保留边缘细节等信息,有利于进一步的红外目标检测等工作。By analyzing the characteristics of infrared images,the gray space of the image can be decomposed into two parts,one part is from object radiation and the other is from atmospheric radiation.Atmospheric gray factor is proposed in this paper to characterize the gray space generated by atmospheric radiation.In order to improve the image quality and enhance the visual effect of the image,by establishing a grayscale mapping model based on the atmospheric gray factor,the image quality degradation caused by atmospheric radiation is effectively eliminated.As to solve the problem that the edge of the enhanced image is rough,this paper uses the original image as the guide to correct the atmospheric gray factor.Compared with the traditional histogram equalization algorithm,algorithm of this paper has more extensive adaptability.In the meantime,this algorithm can preserve the image detail better while enhancing the image contrast,which is beneficial to further infrared target detection.

关 键 词：红外图像增强 灰度空间 大气灰度因子 灰度映射模型 导向滤波 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]