Visible images contain rich texture information, whereas infrared images have significant
contrast. It is advantageous to combine these two kinds of information into a single image so …

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 …

Infrared and visible image fusion aims to describe the same scene from different aspects by
combining complementary information of multi-modality images. The existing Generative …

A good result of infrared and visible image fusion should not only maintain significant
contrast for distinguishing targets from the backgrounds, but also contain rich scene textures …

Infrared and visible image fusion intends to generate a synthetic image with superior scene
representation and better visual perception. The existing deep learning-based fusion …

A single infrared image or visible image cannot clearly present texture details and infrared
information of the scene in poor illumination, bad weather, or other complex conditions …

This paper proposes a new infrared and visible image fusion method based on the densely
connected disentangled representation generative adversarial network (DCDR-GAN), which …

Generative adversarial network (GAN) has shown great potential in infrared and visible
image fusion. The existing GAN-based methods establish an adversarial game between …

Methods based on generative adversarial network (GAN) have been widely used in infrared
and visible images fusion. However, these methods cannot perceive the discriminative parts …

Image fusion synthesizes a new image from multiple images of the same scene. The
synthesized image should be suitable for human visual perception and follow-up high-level …