Abstract. Most existing dehazing approaches employ image priors such as a dark channel prior, which may be violated in the nighttime. In addition, these approaches perform dehazing directly on the original hazy image, which usually results in detail blurring and noise amplifying. To address both issues, an effective single nighttime image haze removal approach is presented. We first decompose the hazy image into a structure layer and a texture layer. Specifically, the dehazing operation is performed only on the structure layer to avoid detail loss and noise amplification. Due to the low frequency characteristics of the haze and the glow of artificial lights, the atmospheric veil is estimated on structure layer dehazing. Furthermore, to eliminate the nonuniform illumination effects, we present an ambient light estimation approach based on multiscale fusion. At the same time, the denoising is performed in the texture layer. Extensive experiments demonstrate that the proposed approach recovers a high-quality, haze-free, and noise-free image with vivid details.

中文翻译：

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保留细节的单个夜间图像去雾

摘要。大多数现有的去雾方法采用图像先验，例如暗通道先验，这可能在夜间被破坏。此外，这些方法直接对原始模糊图像进行去雾处理，通常会导致细节模糊和噪声放大。为了解决这两个问题，提出了一种有效的夜间图像去雾方法。我们首先将朦胧图像分解为结构层和纹理层。具体来说，去雾操作只对结构层进行，以避免细节损失和噪声放大。由于雾霾的低频特性和人造光的辉光，在结构层去雾上估计大气面纱。此外，为了消除不均匀的照明效果，我们提出了一种基于多尺度融合的环境光估计方法。同时在纹理层进行去噪。大量实验表明，所提出的方法可以恢复具有生动细节的高质量、无雾霾和无噪声图像。