In image fusion, the most desirable information is obtained from multiple images of the same
scene and merged to generate a composite image. This resulting new image is more …

Multi-modality image fusion provides more comprehensive and sophisticated information in
modern medical diagnosis, remote sensing, video surveillance, and so on. This paper …

Visible and infrared image fusion (VIF) has attracted a lot of interest in recent years due to its
application in many tasks, such as object detection, object tracking, scene segmentation …

Existing image fusion methods are typically limited to aligned source images and have to
“tolerate” parallaxes when images are unaligned. Simultaneously, the large variances …

As a result of several successful applications in computer vision and image processing,
sparse representation (SR) has attracted significant attention in multi-sensor image fusion …

The fusion of infrared and visible images of the same scene aims to generate a composite
image which can provide a more comprehensive description of the scene. In this paper, we …

Multi-modality image fusion is an effective technique to fuse the complementary information
from multi-modality images into an integrated image. The additional information can not only …

Medical image fusion technique plays an an increasingly critical role in many clinical
applications by deriving the complementary information from medical images with different …

In this letter, a sparse representation (SR) model named convolutional sparsity based
morphological component analysis (CS-MCA) is introduced for pixel-level medical image …

As a powerful assistance technique for biomedical diagnosis, multimodal medical image
fusion has emerged as a hot topic in recent years. Unfortunately, the trade-off among fusion …