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 …

Image fusion is a technique used to merge two or more source images into a single image
that incorporates more details than the originals and still offering an accurate depiction …

Accurately distinguishing the types of tea is of great significance to the pricing, production,
and processing of tea. The similarity of the internal spectral characteristics and appearance …

Generating the decision map with accurate boundaries is the key to fusing multi-focus
images. In this paper, we introduce edge-preservation (EP) techniques into neural networks …

Image fusion technology aims to obtain a comprehensive image containing a specific target
or detailed information by fusing data of different modalities. However, many deep learning …

In this paper, a two-scale transform-based fusion model for visible and infrared images is
proposed to integrate thermal target regions from infrared images and preserve pleasing …

Image fusion techniques have been widely used for multi-modal medical image fusion tasks.
Most existing methods aim to improve the overall quality of the fused image and do not focus …

Multimodal medical image fusion aims to fuse images with complementary multisource
information. In this paper, we propose a novel multimodal medical image fusion method …

Aiming at the current multimodal medical image fusion methods that cannot fully
characterize the complex textures and edge information of the lesion in the fused image, a …

Medical image fusion plays a pivotal role in facilitating clinical diagnosis. However, the
quality of input medical images may be marred by noise, low contrast, and lack of …