低照度短波红外图像增强算法
投稿时间:2019-06-18  修订日期:2020-11-11  点此下载全文
引用本文:张瑞,汤心溢,李争.低照度短波红外图像增强算法[J].红外与毫米波学报,2020,39(6):818~824].ZHANG Rui,TANG Xin-Yi,LI Zheng.Research on low illumination shortwave infrared image enhancement algorithm[J].J.Infrared Millim.Waves,2020,39(6):818~824.]
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作者单位E-mail
张瑞 中国科学院大学北京 100049
中国科学院上海技术物理研究所上海 200083
中国科学院红外探测与成像技术重点实验室上海 200083 
1546853078@qq.com 
汤心溢 中国科学院上海技术物理研究所上海 200083
中国科学院红外探测与成像技术重点实验室上海 200083 
tangxini@189.cn 
李争 中国科学院上海技术物理研究所上海 200083
中国科学院红外探测与成像技术重点实验室上海 200083 
 
基金项目:十三五预研课题(HJJ2019-0089)
中文摘要:为了拓展非制冷短波红外探测器在弱光夜视观测方面的应用,开展了针对短波红外低照度成像的研究。提出了一种新的图像增强方法抑制图像噪声增强图像细节进而改善图像质量。使用3D降噪(3DNR(3D Noise reduction))算法,将多尺度高斯差分法结合边缘保持滤波器最大限度的分离图像高频信息与隐藏噪声,再针对图像进行自适应灰度映射。实验结果表明:该算法显著地抑制了在低照度下图像的时域噪声,丰富了短波红外图像的细节,改善了短波红外的夜视显示效果。
中文关键词:低照度  短波红外  视网膜模型  图像增强  降噪
 
Research on low illumination shortwave infrared image enhancement algorithm
Abstract:In order to expand application of uncooled short wave infrared array detectors for low-light night vision, a research on low-light imaging of short-wave infrared have carried out. This paper proposes a new image enhancement method to suppress image noise, enhance image details and improve image quality. The proposed schemes use 3DNR (3D noise reduction), combine the multi-scale Gaussian differential method with the edge preserving filter to separate the high-frequency information and hidden noise of the image to the maximum extent, and then carry out the adaptive grayscale mapping for the image. The experimental results demonstrate that the proposed algorithm outperforms some state-of-the-art algorithms, and it can achieve outstanding image enhancement performance and suppress the time-domain noise of the image under low-light illumination.
keywords:low Illumination  short wave infrared (SWIR)  retinex model  image enhancement  noise reduction
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