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 …

In this paper, we proposed a new end-to-end model, termed as dual-discriminator
conditional generative adversarial network (DDcGAN), for fusing infrared and visible images …

Image fusion integrates a series of images acquired from different sensors, eg, infrared and
visible, outputting an image with richer information than either one. Traditional and recent …

Existing image fusion methods are typically limited to aligned source images and have to
“tolerate” parallaxes when images are unaligned. Simultaneously, the large variances …

Recent advances in deep networks have gained great attention in infrared and visible image
fusion (IVIF). Nevertheless, most existing methods are incapable of dealing with slight …

In this study, we propose a target-enhanced multiscale transform (MST) decomposition
model for infrared and visible image fusion to simultaneously enhance the thermal target in …

In this article, we propose a novel decomposition method by applying disentangled
representation for visible and infrared image fusion (DRF). According to the imaging …

Image fusion plays a critical role in a variety of vision and learning applications. Current
fusion approaches are designed to characterize source images, focusing on a certain type of …

This paper proposes an effective infrared and visible image fusion method based on a
texture conditional generative adversarial network (TC-GAN). The constructed TC-GAN …

Fusion technologies have rapidly evolved. These technologies are normally customized
according to the needs of domains. Despite a large number of publications on intelligence …