Multimodal fusion focuses on integrating information from multiple modalities with the goal of
more accurate prediction, which has achieved remarkable progress in a wide range of …

Existing infrared and visible image fusion methods based on attention mechanisms can
perceive the most discriminative regions of the two images. However, the disadvantage is …

In this paper, a robust infrared and visible image fusion scheme that joins a dual-branch
multi-receptive-field neural network and a color vision transfer algorithm is designed to …

Medical image fusion technology is an essential component of computer-aided diagnosis,
which aims to extract useful cross-modality cues from raw signals to generate high-quality …

Due to the significant difference in the structure of infrared and visible images, most of the
existing algorithms use globally consistent strategy, which may weaken the contrast of the …

Thermal infrared and multispectral visible remote sensing image fusion combines thermal
image information with corresponding visible scene content to generate a better …

Current researches in the infrared and visible image fusion task tend to focus on designing
decomposition or fusion schemes for improving the feature preservation performance …

Due to the sampling and pooling operations, deep learning-based infrared and visible-light
image fusion methods often result into detail loss problem, especially under low illumination …

This paper proposes a dual-weighted polarization image fusion method based on quality
assessment and attention mechanisms to fuse the intensity image (S0) and the degree of …