大气中微小颗粒(如雾、霾等)的散射作用会使户外场景拍摄的图像发生退化,造成图像质量下降。图像去雾可以提升图像对比度,增加场景能见度,校正颜色失真,改善视觉效果。但是图像去雾经常会出现明显的噪声放大现象,尤其是无穷远处的天空区域最为严重。针对这一问题,提出了一种去雾过程中的噪声抑制方法。以传输率图像为指导,采用滤波半径变化的双边滤波对雾天图像进行模糊。再计算新的传输率图像,代入雾天成像模型,得到去噪后复原图像。结合噪声评价方法,实验结果验证了该方法的噪声抑制效果。
The scattering of particles (e.g. haze particles and fog droplets) in the atmosphere degrades images of outdoor scenes and further harms image quality. Image dehazing can significantly gain contrast, increase scene visibility, correct color shift introduced by the airlight and improve visual effect. Nonetheless, image dehazing is prone to noise amplification. Noise of the dehazed image is obvious in regions with low transmission, especially for distant sky region. A noise inhibition method during image dehazing was proposed to solve this problem. The hazy image was smoothed by the bilateral filter with varying radius which was adapted to the transmission map. The new transmission map was calculated again corresponding to the smoothed hazy image, and then used to estimate the denoised recovery image. Combining the noise estimation method for single color image, experimental results demonstrate our method's performance with noise inhibition.