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 …

Abstract Fusion of Medical Images is a simple process to register and merge various images
from various modalities of images to enhance the quality of image and reduction in the …

Image fusion is the generation of an informative image that contains complementary
information from the original sensor images, such as texture details and attentional targets …

Focus measurement, one of the key tasks in multifocus image fusion (MFIF) frameworks,
identifies the clearer parts of multifocus images pairs. Most of the existing methods aim to …

Multi-focus image fusion (MFIF) is an image enhancement technique that investigates how
to obtain a fully focused image from multiple defocus images, providing fundamental …

In the field of medical imaging, high-quality multi-modal image fusion is crucial for improving
diagnostic accuracy. By integrating information from different imaging modalities, medical …

Infrared and visible image fusion, as a typical image enhancement task, aims to generate an
image containing complementary information. Existing deep learning-based methods …

Multi-focus image fusion (MFIF) aims to break the limitations of physical devices and
integrate different focused regions from multiple source images into a single fully focused …

The goal of infrared and visible image fusion is to generate an informative image that
preserves the complementary information of the two types of source images, such as texture …

Multi-focus image fusion is a technique that combines multiple out-of-focus images to
enhance the overall image quality. It has gained significant attention in recent years, thanks …