IDRLP: Image Dehazing Using Region Line Prior
IDRLP: Image Dehazing Using Region Line Prior
复制标题
IDRLP：使用区域线优先进行图像去雾
DOI：
10.1109/tip.2021.3122088
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发表时间：
2021-10
影响因子：
10.6
通讯作者：
Dacheng Tao
中科院分区：
文献类型：
--
作者：
Mingye Ju;Can Ding;Charles A. Guo;Wenqi Ren;Dacheng Tao
在这项工作中，提出了一种新的和超鲁棒的单图像去雾方法称为IDRLP。据观察，当一个图像被划分为$n$区域，每个区域具有类似的场景深度，模糊的图像和其无雾对应的亮度与场景深度呈正相关。基于这一观察，这项工作确定，模糊输入和其haze-free对应表现出准线性关系后，执行此区域分割，这被称为区域线先验（RLP）。通过将RLP与大气散射模型（ASM）相结合，可以容易地获得恢复公式（RF），其中只有两个未知参数，即，线性函数的斜率和大气光。然后设计了一个考虑两个约束条件的二维联合优化函数来求解RF。与其他类似的作品不同，这种“联合优化”策略有效地利用了整个图像的信息，从而获得了具有超高鲁棒性的更准确的结果。最后，在射频部分引入引导滤波器，消除区域分割带来的不利干扰。建议RLP和IDRLP从不同的角度进行评估，并与相关国家的最先进的技术进行比较。大量的分析验证了IDRLP的优越性，国家的最先进的图像去雾技术的恢复质量和效率。软件版本可在https://sites.google.com/site/renwenqi888/上获得。
In this work, a novel and ultra-robust single image dehazing method called IDRLP is proposed. It is observed that when an image is divided into $n$ regions, with each region having a similar scene depth, the brightness of both the hazy image and its haze-free correspondence are positively related with the scene depth. Based on this observation, this work determines that the hazy input and its haze-free correspondence exhibit a quasi-linear relationship after performing this region segmentation, which is named as region line prior (RLP). By combining RLP and the atmospheric scattering model (ASM), a recovery formula (RF) can be easily obtained with only two unknown parameters, i.e., the slope of the linear function and the atmospheric light. A 2D joint optimization function considering two constraints is then designed to seek the solution of RF. Unlike other comparable works, this “joint optimization” strategy makes efficient use of the information across the entire image, leading to more accurate results with ultra-high robustness. Finally, a guided filter is introduced in RF to eliminate the adverse interference caused by the region segmentation. The proposed RLP and IDRLP are evaluated from various perspectives and compared with related state-of-the-art techniques. Extensive analysis verifies the superiority of IDRLP over state-of-the-art image dehazing techniques in terms of both the recovery quality and efficiency. A software release is available at https://sites.google.com/site/renwenqi888/.