Recent advances in deep learning have shown excellent performance in various scene
understanding tasks. However, in some complex environments or under challenging …

Haze usually causes severe interference to image visibility. Such degradation on images
troubles both human observers and computer vision systems. To seek high-quality images …

Haze, a common kind of bad weather caused by atmospheric scattering, decreases the
visibility of scenes and degenerates the performance of computer vision algorithms. Single …

One of the key ingredients of any physically based rendering system is a detailed
specification characterizing the interaction of light and matter of all materials present in a …

Heavy haze/noise can cause unpleasant information loss in near infrared (NIR) and visible
(VI) image fusion. To generate high-quality fused images, this paper proposes a detail …

We propose a real-time image fusion method using pre-trained neural networks. Our method
generates a single image containing features from multiple sources. We first decompose …

Integrating the information of infrared and visible images without human supervision is a
long-standing problem. A key technical challenge in this domain is how to extract features …

The visible (VS) and near-infrared (NIR) image fusion is a common approach to improve
image visibility, which saves rich scene details and similar colors to the VS image in fused …

Thermal imaging has a variety of applications, from agricultural monitoring to building
inspection to imaging under poor visibility, such as in low light, fog, and rain. However …

With the unavailability of scene depth information, single-sensor dehazing methods based
on deep learning or prior information do not effectively work in dense foggy scenes. An …