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 …

Muti-focus image fusion is the extraction of focused regions from different images to create
one all-in-focus fused image. The key point is that only objects within the depth-of-field have …

Multimodal image fusion combines information from multiple modalities to generate a
composite image containing complementary information. Multimodal image fusion is …

Image fusion is a long-established and well-known study area of digital image processing.
The reason is its substantial approach in several practical applications in which multi-focus …

The target-level infrared and visible image fusion aims to prominently retain the feature of
target areas in the entire scene of fusion results. Nonetheless, most of existing fusion …

In this paper, a novel self-supervised mask-optimization model, termed as SMFuse, is
proposed for multi-focus image fusion. In our model, given two source images, a fully end-to …

Because infrared images emphasize thermal targets while visible images provide a wealth
of textural information, fusing the two modal images improves the human perception of the …

The general aim of multi-focus image fusion is to gather focused regions of different images
to generate a unique all-in-focus fused image. Deep learning based methods become the …

Multi-focus image fusion (MFIF) is an image enhancement technology with broad application
prospects that can effectively extend the depth-of-field of optical lenses. This paper presents …

Multi-focus image fusion (MFIF) aims to utilize multiple images with different focal lengths to
fuse into a single full-focus image. This process enhances the realism and clarity of the …