Pixel-level image fusion, which merges different modal images into an informative image,
has attracted more and more attention. Despite many methods that have been proposed for …

Infrared (IR) and visual (VI) image fusion is designed to fuse multiple source images into a
comprehensive image to boost imaging quality and reduce redundancy information, which is …

In the principle of lens imaging, when we project a three-dimensional object onto a
photosensitive element through a convex lens, the point intersecting the focal plane can …

Deep learning is a rapidly developing approach in the field of infrared and visible image
fusion. In this context, the use of dense blocks in deep networks significantly improves the …

Visual object tracking has attracted widespread interests recently. Due to the complementary
features provided by visible and infrared images, fusion tracking based on visible and …

The field of multimodal medical image fusion has made huge progress in the past decade.
However, previous methods always suffer from color distortion, blurring, and noise. To …

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion.
To better preserve the significant information of the infrared and visible images in the final …

Multi-focus image fusion aims to extract the focused regions from multiple partially focused
images of the same scene and then combine them together to produce a completely focused …

Image fusion is an important task for computer vision as a diverse range of applications are
benefiting from the fusion operation. The existing image fusion methods are largely …

Multi-exposure image fusion (MEF) is an important area in computer vision and has attracted
increasing interests in recent years. Apart from conventional algorithms, deep learning …