在雾、霾等天气条件下,大气粒子的散射与吸收作用严重影响了监视图像的对比度与清晰度。本文讨论了基于大气光幕的去雾算法原理,针对双边滤波方法在估计大气光幕时产生梯度反转效应,提出一种改进的基于大气光幕单幅图像去雾算法,首先简化大气散射模型,然后利用各项异性扩散滤波方法估计大气光幕,可以很好地解决双边滤波方法的不足之处,最后,在算法中引入一种容差机制,针对天空区域处的大气光幕,纠正错误的估计,色彩失真现象被有效地克服。实验结果表明,改进后的算法显著地提高图像去雾的视觉效果。
Under a haze and mist weather condition,the scattering and absorption due to atmospheric particles tremendous influence on contrast and visibility of the surveillance images.In this paper,the image fog removal principle using atmospheric veil is discussed,for the bilateral filter leads to gradient reversal artifacts while atmospheric veil estimate is refined using a bilateral filtering,an improved single image de-hazing method using atmospheric veil is proposed.Firstly,the atmospheric scattering model was simplified.Then,the estimated atmospheric veil is refined using an anisotropic diffusion filtering to overcome the weakness of the bilateral filter.Finally,the tolerance mechanism is used in algorithm,the error estimates of atmospheric veil in sky region is corrected,so as to overcome the color distortion in these region.Experimental results show that improved algorithm can efficiently improve the visual effects of de-hazed image.