单幅雾天图像的同步去噪与复原

在单幅雾天图像复原中图像不可避免地存在大量噪声,这会对复原结果带来很大影响.文中提出一种基于联合双边滤波的单幅雾天图像同步去噪和复原算法.该算法首先根据暗通道先验假设估计出可反映场景深度特性的初始传输图.其次,利用联合双边滤波器,在原始图像的引导下对初始的粗糙传输图进行细化,有效降低光晕现象的出现.再使用一次双边滤波求解复原图像,在得到去雾图像的同时实现图像去噪.最后,在滤波过程中引入一个色彩恢复因子,解决复原过程引起的色彩失真问题.文中对各种类型的图片进行对比实验,结果表明该算法能在去雾的同时有效抑制图像中的噪声,并保持较低的计算复杂度.此外,引入的色彩恢复因子也给复原图像带来丰富的色彩.

Simultaneous Dehazing and Denoising of Single Hazing Image

Various noise exists in images in practice,which brings great influence on dehazing results.Aiming at this,single image dehazing algorithm is proposed which can realize simultaneous dehazing and denoising based on joint bilateral filter.Firstly,the initial rough transmission map is estimated based on dark prior.Then,a joint bilateral filter is applied to refine the rough transmission map under the guidance of original image,which decreases the halo artifacts in the dehazing image effectively.Next,another bilateral filter is applied to obtain the dehzaing image,which can realize image denoising at the same time.Finally,a color factor is introduced into the bilateral filtering process to deal with the color distort problem.Various contrastive experimental results verify that the proposed algorithm realizes single image dehazing and denoising simultaneously with low computational costs.Besides,the color factor brings abundant chromatic details in the dehazing results.