Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

The images acquired by a single visible light sensor are very susceptible to light conditions,
weather changes, and other factors, while the images acquired by a single infrared light …

In this article, we propose an infrared and visible image fusion network based on the salient
target detection, termed STDFusionNet, which can preserve the thermal targets in infrared …

In this paper, we present a novel deep learning architecture for infrared and visible images
fusion problems. In contrast to conventional convolutional networks, our encoding network is …

Infrared images can distinguish targets from their backgrounds based on the radiation
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …

In this paper, we propose a new infrared and visible image fusion method based on multi-
scale transformation and norm optimization. In this method, a new loss function is designed …

Infrared images can distinguish targets from their backgrounds on the basis of difference in
thermal radiation, which works well at all day/night time and under all weather conditions. By …

Existing image fusion approaches are committed to using a single deep network to solve
different image fusion problems, achieving promising performance in recent years. However …

TargefTablets can be detected easily from the background of infrared images due to their
significantly discriminative thermal radiations, while visible images contain textural details …

In recent years, deep learning has become a very active research tool which is used in many
image processing fields. In this paper, we propose an effective image fusion method using a …