Visibility enhancement of images captured during hazy weather conditions is highly essential for various important applications like intelligent vehicles, surveillance, remote sensing, etc. In recent years, researchers proposed numerous image-dehazing methods mostly focusing on daytime images’ characteristics. In this work, we have highlighted the dissimilarities among the characteristics of daytime and nighttime hazy images and explained that well-known daytime image-dehazing priors cannot dehaze nighttime hazy images effectively. Following this discussion, we have provided a comprehensive review of existing nighttime image-dehazing methods after grouping them according to different nighttime hazy image models based on which they were designed as their methodologies vastly vary with those models. Thereafter, we have performed comparative qualitative and quantitative analyses of outputs obtained by applying these methods on images belonging to novel N-HAZE database. N-HAZE comprises of both indoor and outdoor real-world nighttime hazy images captured in the presence of haze created by artificial haze machines and corresponding Ground Truth images. Finally, we have concluded our work by stating the existing challenges and future scope of work in this field after analyzing the strengths and limitations of each method. Our main aim behind conducting this survey is to draw the attention of more researchers towards this less explored yet significant research topic and encourage them to design new methods which can solve the existing challenges. To the best of our knowledge, we are the first ones to review the nighttime image-dehazing methods and to design N-HAZE, which is the first database designed for benchmarking these methods.

在朦胧的天气条件下捕获的图像的可视性增强对于诸如智能车辆，监视，遥感等各种重要应用非常重要。近年来，研究人员提出了许多图像去雾方法，这些方法主要着眼于白天图像的特性。在这项工作中，我们强调了白天和夜间朦胧图像特征之间的差异，并解释了众所周知的白天图像去雾先验不能有效地消除夜间朦胧图像。在进行了讨论之后，我们根据不同的夜间模糊图像模型对现有的夜间图像去雾方法进行了分组，从而对其进行了全面的回顾，因为它们的设计方法因其与这些模型的不同而异。之后，我们已经对通过将这些方法应用到属于新型N-HAZE数据库的图像进行的输出进行了比较定性和定量分析。N-HAZE包括在存在人工雾霾机产生的雾霾时捕获的室内和室外真实世界夜间雾霾图像以及相应的Ground Truth图像。最后，在分析每种方法的优势和局限性之后，我们通过阐述该领域中存在的挑战和未来的工作范围来结束我们的工作。我们进行这项调查的主要目的是，吸引更多的研究者关注这个鲜为探索但意义重大的研究课题，并鼓励他们设计出能够解决现有挑战的新方法。据我们所知，