摘要
为提高低照度图像的细节增强效果,本文提出一种基于去雾技术的低照度图像增强算法,首先对低照度图像应用反色操作,然后在反色的图像上执行雾度去除,再次执行反色操作以获得输出图像。随后,在YCbCr色彩空间中,构建一个细节增强网络,用抛物线函数对亮度信息进行增强,拉伸低亮度区域,基本不改变高亮区域的亮度值,保持色彩信息不变,实验证明,本方法可以提高图像的整体细节信息,同时避免了传统方法中出现的为Gmmu问题,具有良好的视觉效果。
To achieve low ilumination image enhancement,this paper proposes a low ilumination image enhancement algorithm based on the technology of fogging,First,the anti color operation is applied to the low illumination image,then the foggy removal is performed on the anti color image,and the anti color operation is executed again to obtain the output image.Then,in the YCbCr color space,a detail enhancement network is constructed,the luminance information is enhanced with the parabolic function,the low brightness region is stretched,the brightness value of the bright region is not changed,and the color information is kept constant.The experiment proves that this method can improve the overall details of the image and avoid the traditional side.The problem appeared in the law has a good visual effect.
作者
彭琼瑶
赵广源
周炳
臧苏东
PENG Qiongyao;ZHAO Guangyuan;ZHOU Bing;ZANG Sudong
出处
《数码设计》
2019年第1期27-30,共4页
Peak Data Science
关键词
低照度
去雾算法
图像增强
抛物线函数
low illumination
De-fog algorithm
Image Enhancement
Parabolic function
