基于AOD-Net改进的单幅图像去雾算法研究

Research on Improved Single Image Defogging Algorithm Based on AOD-Net

针对雾天拍摄图像不清晰的问题,提出了一种基于改进AOD-Net的单幅图像去雾算法。即在已有AOD-Net去雾算法的基础上,针对其存在的参数估计不均导致累计误差,从而使得去雾后的图像色彩失真以及低照度下效果不佳等缺陷,对AOD-Net去雾算法的损失函数进行了改进,同时引入一个低照度增强模块。由实验结果可知,改进的方法在真实图像和人工合成图像上去雾效果都有了较大的提升,有效地提高了图像质量,在PSNR和SSIM指标上均优于其他对比算法。

In order to solve the problem of unclear images taken in fog,a single image defogging algorithm based on improved AOD-Net is proposed.That is,based on the existing AOD-Net defogging algorithm,the loss function of AOD-Net defogging algorithm is improved,and a low illumination enhancement module is introduced at the same time,aiming at the defects that the uneven parameter estimation leads to cumulative error,which leads to the color distortion of the image after defogging and the poor effect under low illumination.From the experimental results,we can see that the improved method has greatly improved the defogging effect in both real images and synthetic images,and effectively improved the image quality,and is superior to other comparison algorithms in terms of PSNR and SSIM indicators.