Jin Zheyan, Feng Huajun, Xu Zhihai, Chen Yueting
State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.
J Imaging. 2023 Jul 28;9(8):153. doi: 10.3390/jimaging9080153.
Nighttime image dehazing presents unique challenges due to the unevenly distributed haze caused by the color change of artificial light sources. This results in multiple interferences, including atmospheric light, glow, and direct light, which make the complex scattering haze interference difficult to accurately distinguish and remove. Additionally, obtaining pairs of high-definition data for fog removal at night is a difficult task. These challenges make nighttime image dehazing a particularly challenging problem to solve. To address these challenges, we introduced the haze scattering formula to more accurately express the haze in three-dimensional space. We also proposed a novel data synthesis method using the latest CG textures and lumen lighting technology to build scenes where various hazes can be seen clearly through ray tracing. We converted the complex 3D scattering relationship transformation into a 2D image dataset to better learn the mapping from 3D haze to 2D haze. Additionally, we improved the existing neural network and established a night haze intensity evaluation label based on the idea of optical PSF. This allowed us to adjust the haze intensity of the rendered dataset according to the intensity of the real haze image and improve the accuracy of dehazing. Our experiments showed that our data construction and network improvement achieved better visual effects, objective indicators, and calculation speed.
由于人工光源颜色变化导致的雾霭分布不均，夜间图像去雾面临着独特的挑战。这会产生多种干扰，包括大气光、光晕和直射光，使得复杂的散射雾霭干扰难以准确区分和去除。此外，获取用于夜间去雾的高清数据对是一项艰巨的任务。这些挑战使得夜间图像去雾成为一个特别具有挑战性的问题。为了应对这些挑战，我们引入了雾霭散射公式，以便更准确地在三维空间中表达雾霭。我们还提出了一种新颖的数据合成方法，利用最新的CG纹理和流明照明技术来构建场景，在其中可以通过光线追踪清晰地看到各种雾霭。我们将复杂的3D散射关系转换为2D图像数据集，以便更好地学习从3D雾霭到2D雾霭的映射。此外，我们改进了现有的神经网络，并基于光学点扩散函数的思想建立了夜间雾霭强度评估标签。这使我们能够根据真实雾霭图像的强度调整渲染数据集的雾霭强度，并提高去雾的准确性。我们的实验表明，我们的数据构建和网络改进在视觉效果、客观指标和计算速度方面都取得了更好的效果。
