Images acquired in poor weather conditions (haze, fog, smog, mist, etc.) are often severely
degraded. In the atmosphere, there exists two types of particles: dry particles (dust, smoke …

随着图像处理技术和计算机视觉技术的蓬勃发展, 对特殊天气下的场景检测和图像处理成为该
领域的重要研究方向. 其中在雾天拍摄的图像容易受雾或霾的影响, 导致图片细节模糊 …

Removing the smog from digital images is a challenging pre-processing tool in various
imaging systems. Therefore, many smog removal (ie, desmogging) models are proposed so …

In the task of haze scene restoration, dark channel prior is the most convincing theory. Its
biggest contribution is to introduce the concept of dark channel map, which is convenient for …

Environmental factors such as fog and haze affect the image quality and make it unsuitable
for automated systems, such as intelligent vehicles, surveillance, and outdoor object …

Deep learning-based object detection has recently received significant attention among
scholars and practitioners. However, the acquired images often suffer from visual quality …

Hazy images suffer from poor visibility and possess low-contrast, degrading the visibility of
the scene. The performance of single-image haze removal methods is limited by priors or …

In this paper, we investigate the challenging task of removing haze from a single natural
image. The analysis on the haze formation model shows that the atmospheric veil has much …

Real-time video defogging has a huge demand in intelligent transportation, advanced driver
assistance systems (ADAS), long-range surveillance, autonomous aerial vehicles and …

Current dehazing methods for unmanned aerial vehicle (UAV) remote sensing images often
have texture detail loss and color distortion problems, especially in highlighted regions. This …