Infrared and visible image fusion aims to synthesize a single fused image that not only
contains salient targets and abundant texture details but also facilitates high-level vision …

Infrared and visible image fusion aims to synthesize a single fused image containing salient
targets and abundant texture details even under extreme illumination conditions. However …

In the image fusion field, the design of deep learning-based fusion methods is far from
routine. It is invariably fusion-task specific and requires a careful consideration. The most …

Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

It is very challenging for various visual tasks such as image fusion, pedestrian detection, and
image-to-image translation in low light conditions due to the loss of effective target areas. In …

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 …

As a vital image enhancement technology, infrared and visible image fusion aims to
generate high-quality fused images with salient targets and abundant texture in extreme …

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 …

Deep learning based fusion methods have been achieving promising performance in image
fusion tasks. This is attributed to the network architecture that plays a very important role in …

Infrared and visible image fusion technologies make full use of different image features
obtained by different sensors, retain complementary information of the source images during …