Image fusion integrates a series of images acquired from different sensors, eg, infrared and
visible, outputting an image with richer information than either one. Traditional and recent …

Image fusion plays a pivotal role in numerous high-level computer vision tasks. Existing
deep learning-based image fusion methods usually leverage an implicit manner to achieve …

Image fusion techniques aim to generate more informative images by merging multiple
images of different modalities with complementary information. Despite significant fusion …

Multi-modality (MM) image fusion aims to render fused images that maintain the merits of
different modalities, eg, functional highlight and detailed textures. To tackle the challenge in …

Infrared and visible image fusion, a hot topic in the field of image processing, aims at
obtaining fused images keeping the advantages of source images. This paper proposes a …

Infrared and visible image fusion targets to provide an informative image by combining
complementary information from different sensors. Existing learning-based fusion …

Infrared and visible image fusion has gained ever-increasing attention in recent years due to
its great significance in a variety of vision-based applications. However, existing fusion …

Infrared and visible image fusion aims to integrate complementary information from different
types of images into one image. The existing image fusion methods are primarily based on …

A single infrared image or visible image cannot clearly present texture details and infrared
information of the scene in poor illumination, bad weather, or other complex conditions …

Infrared image retains typical thermal targets while visible image preserves rich texture
details, image fusion aims to reconstruct a synthesized image containing prominent targets …