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 …

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

Multi-focus image fusion (MFIF) is an important area in image processing. Since 2017, deep
learning has been introduced to the field of MFIF and various methods have been proposed …

By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …

As is well known, activity level measurement and fusion rule are two crucial factors in image
fusion. For most existing fusion methods, either in spatial domain or in a transform domain …

This research focuses on the discovery and localization of hidden objects in the wild and
serves unmanned systems. Through empirical analysis, infrared and visible image fusion …

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 …

Pixel-level image fusion is designed to combine multiple input images into a fused image,
which is expected to be more informative for human or machine perception as compared to …

Fusing infrared and visible images can provide more texture details for subsequent object
detection task. Conversely, detection task furnishes object semantic information to improve …

The goal of infrared (IR) and visible image fusion is to produce a more informative image for
human observation or some other computer vision tasks. In this paper, we propose a novel …