基于Retinex和双边滤波的NSCT域遥感图像去雾
Remote sensing image defogging in NSCT domaim based on Ret-inex and bilateral filtering
仲会娟 1马秀荣 2董亚梦3
作者信息
- 1. 阳光学院人工智能学院,福建福州 350015;河北工程技术学院网络与通信学院,河北石家庄 050000
- 2. 阳光学院人工智能学院,福建福州 350015
- 3. 河北工程技术学院网络与通信学院,河北石家庄 050000
- 折叠
摘要
针对遥感图像易受天气影响导致整体对比度差、轮廓细节不清、视觉效果不佳等问题,本文提出基于非下采样轮廓波变换(non-subsampled contourlet transform,NSCT)算法,结合Retinex与双边滤波实现图像去雾增强.首先,对有雾图像各通道分别进行NSCT分解获得高频与低频子带.然后,低频子带中采用Retinex算法和线性增强处理,提高图像亮度均匀性和灰度动态范围;高频子带中引入双边滤波和梯度增强处理,滤除噪声的同时保留并增强图像边缘轮廓.最后,融合处理后的低频子带和高频子带实现去雾增强,并通过白平衡算法保持图像色彩一致性和准确性.实验结果表明:对不同算法实施对比实验,平均梯度提高17.51,均值适中.该算法在去雾过程中可以有效增强高频细节、改善对比度,使得图像质量明显提升.
Abstract
Aiming at the problems of poor overall contrast,unclear contour details and poor visual effect caused by weather in remote sensing images,a scheme which is based on non-subsampled contourlet transform(NSCT)algorithm and combined with Retinex and bilateral filtering,is proposed to achieve image dehazing enhancement.Firstly,NSCT decomposition is performed on each channel of the hazy image to obtain high frequency and low frequency subbands.Then,Retinex algorithm and linear enhancement processing are used in the low frequency subband to improve the image brightness uniformity and gray dynamic range.The bilateral filtering and gradient enhancement are used in the high frequency subbands to filter out noise while retaining and enhancing the image edge contour.Finally,the low frequency and high frequency subbands are fused to achieve dehazing enhancement,and the white balance algorithm is used to maintain the consistency and accuracy of the image color.The experiments of different algorithm show that the average gradient is improved by 17.51,and the mean value is moderate.In the process of denoising,the proposed algorithm can effectively enhance high frequency details and improve contrast,leading to noticeable improvement in image quality.
关键词
图像去雾/非下采样轮廓波变换(NSCT)/双边滤波/梯度增强/Retinex算法Key words
image dehazing/non-subsampled contourlet transform(NSCT)/bilateral filtering/gradient enhancement/Retinex algorithm引用本文复制引用
基金项目
福建省中青年教师教育科研项目(JAT200860)
出版年
2024
NETL
NSTL
万方数据