In this work we propose HR-Dehazer, a novel and accurate method for image dehazing. An
encoder-decoder neural network is trained to learn a direct mapping between a hazy image …

摘要散射介质广泛存在于自然界中, 透过散射介质成像在医学, 自动驾驶, 国家安全等领域具有
重要的科学意义和应用价值. 简要综述了散射成像技术的发展, 从弹道光和散射光的角度出发 …

In this paper, we explore the problem of single-image haze removal based on retinex model
and new deep retinex decomposition architecture. Reformulating dehazing as reverse …

Image processing is a very fundamental technique in the field of low-level vision. However,
with the development of deep learning over the past five years, most low-level vision …

On the one hand, the dehazing task is an ill-posedness problem, which means that no
unique solution exists. On the other hand, the dehazing task should take into account the …

Enhancing visual quality for underexposed images is an extensively concerning task that
plays an important role in various areas of multimedia and computer vision. Most existing …

Underwater imaging poses significant challenges as water alters the behavior of light in
comparison to air or vacuum. Therefore, it is crucial to effectively utilize the unique …

Most existing dehazing networks rely on synthetic hazy-clear image pairs for training, and
thus fail to work well in real-world scenes. In this paper, we deduce a reformulated …

In the field of single image defogging, there are two main methods. One is the image
restoration method based on the atmospheric scattering theory which can recover the image …

Adopting local patches for varying haze conditions is crucial for optimizing the performance
in single image dehazing. We propose a novel two-fold method with a prime focus on self …