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 …

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 (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 …

The images captured by the cameras contain distortions, misclassified pixels, uncertainties
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input …

Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …

Due to the rapid development of artificial intelligence technology, industrial sectors are
revolutionizing in automation, reliability, and robustness, thereby significantly increasing …

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 …

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 …