基于自适应Gamma校正的红外图像增强算法  

Infrared image enhancement algorithm based on adaptive Gamma correction

作　　者：蔡美芳[1] 万里勇[1,2] CAI Meifang;WAN Liyong(School of Information and Artificial Intelligence,Nanchang Institute of Science and Technology,Nanchang 330108,China;Management Science and Engineering Research Center,Jiangxi Normal University,Nanchang 330022,China)

机构地区：[1]南昌工学院信息与人工智能学院,江西南昌330108 [2]江西师范大学管理科学与工程研究中心,江西南昌330022

出　　处：《光学技术》2022年第4期486-491,共6页Optical Technique

基　　金：江西省高等学院教学改革研究课题(JXJG-20-27-10);江西省一流专业建设项目“南昌工学院电子信息工程特色专业”;江西省教育科学“十三五”规划课题(19YB266)。

摘　　要：为了进一步提升红外图像的亮度和对比度,同时保持图像的自然效果,提出了基于自适应Gamma校正的红外图像增强算法。用改进的双边滤波作为Retinex的中心环绕函数,以提取红外图像的低频和高频部分,即基础层和细节层。对基础层图像进行自适应于暗区像素占比的Gamma校正,以提升图像的亮度和清晰度,而对细节层图像进行自适应的分段线性拉伸,进一步提升图像的对比度。实验结果证明了本文方法的有效性,相对于现有的方法,本文方法增强后的视觉效果更清晰、细节信息更丰富。In order to further improve the brightness and contrast of the infrared image while maintaining the natural effect of the image, an infrared image enhancement method based on adaptive Gamma correction is proposed. The improved bilateral filter is used as the central surround function of Retinex to extract the low-frequency and high-frequency parts of the infrared image, that is, the base layer and the detail layer. Gamma correction adaptive to the proportion of pixels in the dark area is performed on the base layer image, so as to improve the brightness and definition of the image, and adaptive piecewise linear stretching is applied to the detail layer image to further improve the contrast of the image. Experimental results confirm the effectiveness of this method, compared with the existing methods, the visual effect of this method is clearer, and the detail information is richer.

关 键 词：红外图像 图像增强 RETINEX 自适应Gamma校正 线性拉伸 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]