Abstract Multi-Focus Image Fusion (MFIF) is a method that combines two or more source
images to obtain a single image which is focused, has improved quality and more …

Infrared and visible image fusion is an effective image processing technique to obtain more
comprehensive information, which can help people better understand various scenarios. In …

In recent years, extensive multimodal medical image fusion algorithms have been proposed.
However, existing methods are primarily based on specific transformation theories. There …

We present a novel fusion method based on a multi-task robust sparse representation
(MRSR) model and spatial context information to address the fusion of multi-focus gray-level …

Infrared and visible images are a pair of multi-source multi-sensors images. However, the
infrared images lack structural details and visible images are impressionable to the imaging …

Multi-modality image fusion refers to generating a complementary image that integrates
typical characteristics from source images. In recent years, we have witnessed the …

Medical image fusion aims to integrate the complementary information captured by images
of different modalities into a more informative composite image. However, current study on …

How to effectively preserve the fine-scale details of the image when noises are suppressed
is one of the great challenges faced by scholars in the field of noisy image fusion. The …

Medical image fusion is one of the hot research in the field of medical imaging and radiation
medicine, and is widely recognized by medical and engineering fields. In this paper, a new …

This study proposes a novel medical image fusion approach based on the segment graph
filter (SGF) and sparse representation (SR). Specifically, using the SGF, source images are …