Image fusion, which refers to extracting and then combining the most meaningful information
from different source images, aims to generate a single image that is more informative and …

Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

This study proposes a novel general image fusion framework based on cross-domain long-
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …

Multi-focus image fusion (MFF) is an effective way to eliminate the out-of-focus blur
generated in the imaging process. The difficulties in distinguishing different blur levels and …

The image fusion methods based on deep learning has become a research hotspot in the
field of computer vision in recent years. This paper reviews these methods from five aspects …

Multi-focus image fusion methods can be mainly divided into two categories: transform
domain methods and spatial domain methods. Recent emerged deep learning (DL)-based …

In infrared and visible image fusion (IVIF), prior knowledge constraints established with
image-level information often ignore the identity and differences between source image …

Infrared and visible image fusion technology aims to integrate the heat source information of
infrared image into the visible image to generate a more informative image. Many fusion …

As an effective technique to extend the depth-of-field (DOF) of optical lenses, multi-focus
image fusion has recently become an active topic in image processing community. However …

In deep learning (DL)-based multifocus image fusion, effective multiscale feature learning is
a key issue to promote fusion performance. In this article, we propose a novel DL model …