基于暗原色及入射光假设的单幅图像去雾  

Single-image dehazing based on dark channel and incident light assumption

作　　者：於敏杰 张浩峰[1] 

机构地区：[1]南京理工大学计算机科学与工程学院,南京210094

出　　处：《中国图象图形学报》2014年第12期1812-1819,共8页Journal of Image and Graphics

基　　金：国家自然科学基金项目(61101197);水下机器人技术国防科技重点实验室基金项目(9140C270205120C2701)

摘　　要：目的雾是一种常见的天气状况,针对雾能使图像中的景物对比度降低、表面颜色退化的问题,提出一种基于入射光假设的单幅图像去雾方法。方法首先利用全局暗原色进行初步去雾,从而使图像透射率处于[0,1]范围内;然后利用雾天光照均匀的特点以及Retinex的照度估计原理进行透射图的估计;最后利用透射图以及初步去雾图像得到复原图像。结果与He算法、Fattal算法的对比实验结果显示,该算法获得的复原图像细节清晰,颜色自然。与引导滤波优化后的He去雾算法相比,本文算法速度提高了93%。结论大量对比实验结果表明,本文算法能够显著恢复雾天降质图像,对于薄雾和浓雾同样有效,具有广泛的适用性,且算法原理简单。此外,本文算法也同样适用于灰度图。Objective Fog is a common condition that reduces the contrast of an image, bleaches the surface color, and con- siderably reduces the value of outdoor images. To address this problem, we propose a defogging method for a single degrad- ed image on the basis of dark channel and incident light assumption. Method We scan the image with a window to deter- mine the window with the maximum mean brightness. We use the obtained average value as the atmosphere light. The dark channel prior assumption raised by He is not suitable to images that contain a large scene, so we weaken the assumption. We assume that a channel of a pixel whose value is zero exists. Basing on this assumption, we identify the darkest pixel value in the entire image and use the darkest pixel value as the global dark channel. We use the ratio of the grayscale of the point to the atmospheric light as the basis transmission of the image. Using this basis transmission, we conduct the initial dehazing. The transmission rate of the image will then be stretched to the [ 0, 1 ] range. Images taken under a foggy weather almost have no shadow. We therefore assume that the incident light during a foggy day is uniform. We estimate the transmission by using a multi-scale approach combined with retinex theory that uses Gaussian convolution to estimate illumi- nation. According to the haze imaging model, we can recover a high-quality, haze-free image by using this transmission map and the initial dehazing image. Result By weakening the dark channel prior assumption of He, we considerably im- prove its accuracy and perform the initial dehazing on the basis of the weakened assumption. Unlike in other methods, the transmission map of our algorithm does not exhibit an apparent object contour. The fuzzy transmission map is obviously rea-sortable according to the scattering characteristic of fog. Experimental results indicate that the algorithm can provide an ac- curate estimation of the transmission, and the restored images show natural colors and clear details. The alg

关 键 词：去雾 多尺度 照度估计 RETINEX 入射光假设 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]