摘要
夜间图像存在光照不均匀、整体亮度较低、色偏严重的现象,且人工光源附近存在光晕。现有的去模糊模型和算法在光照不均匀情况下,常通过估计光照图来去除光照不均匀的影响。通过使用径向基函数神经网络训练提取光照强度,提出了基于光照估计的夜间图像去模糊算法。针对光照不均匀的问题,通过估计光照分布图来去除不均匀光照的影响,计算得到成像过程中的调制传递函数(MTF)。以计算所得传输图像退化模型的点扩散函数作为先决条件,结合半盲图像复原的数学模型对目标图像进行处理,以提高夜视探测的成像质量。将所提方法与传统盲复原方法及基于深度神经网络的图像复原方法进行主客观比较,实验所得复原图像及数据验证了该方法的有效性,复原图像的质量得到明显提升。
The illumination of the nighttime image is uneven,the overall brightness is low,the color deviation is large,and there is halo near the artificial light source.Existing deblurring models and algorithms often remove the effects of uneven illumination by estimating the illumination map in the case of uneven illumination.By combining the deep learning method with the radial basis function neural network,the illumination intensity was extracted,and the night image deblurring algorithm based on illumination estimation was proposed.For the problem of uneven illumination,the modulation transfer function(MTF)in the imaging process is calculated by estimating the illumination map.Taking the point diffusion function of the transport degrada-tion model as prior knowledge,combining the mathematical model of semi-blind image restoration method,the target image is processed to improve the quality of night vision imaging.In addition,the effectiveness of this method is verified by comparing with the traditional blind restoration method,and the image quality is improved evidently.
作者
邹鹏
谌雨章
陈龙彪
曾张帆
ZOU Peng;CHEN Yu-zhang;CHEN Long-biao;ZENG Zhang-fan(School of Computer Science and Information Engineering,Hubei University,Wuhan 430062,China)
出处
《计算机科学》
CSCD
北大核心
2019年第S11期329-333,340,共6页
Computer Science
基金
国家自然科学基金(61601175)
湖北省大学生创新训练项目基金(201810512051,201710512051)资助
关键词
夜间图像复原
光照预测
径向基函数神经网络
调制传递函数
半盲图像复原
Night vision image restoration
Lighting prediction
Radial basis function neural network
Modulation transfer function
Semi-blind image restoration
