Image fusion meets deep learning: A survey and perspective
Image fusion, which refers to extracting and then combining the most meaningful information
from different source images, aims to generate a single image that is more informative and …
from different source images, aims to generate a single image that is more informative and …
Current advances and future perspectives of image fusion: A comprehensive review
Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …
world than a single modality alone. Infrared images discriminate targets with respect to their …
Deep learning-based multi-focus image fusion: A survey and a comparative study
X Zhang - IEEE Transactions on Pattern Analysis and Machine …, 2021 - ieeexplore.ieee.org
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 …
learning has been introduced to the field of MFIF and various methods have been proposed …
Memory-augmented deep conditional unfolding network for pan-sharpening
Pan-sharpening aims to obtain high-resolution multispectral (MS) images for remote sensing
systems and deep learning-based methods have achieved remarkable success. However …
systems and deep learning-based methods have achieved remarkable success. However …
Efficient and model-based infrared and visible image fusion via algorithm unrolling
Infrared and visible image fusion (IVIF) expects to obtain images that retain thermal radiation
information from infrared images and texture details from visible images. In this paper, a …
information from infrared images and texture details from visible images. In this paper, a …
Panchromatic and multispectral image fusion via alternating reverse filtering network
Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to
super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to …
super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to …
End-to-end learning for simultaneously generating decision map and multi-focus image fusion result
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 …
to generate a unique all-in-focus fused image. Deep learning based methods become the …
Rethinking the effectiveness of objective evaluation metrics in multi-focus image fusion: A statistic-based approach
As an effective technique to extend the depth-of-field (DOF) of optical lenses, multi-focus
image fusion has recently become an active topic in image processing community. However …
image fusion has recently become an active topic in image processing community. However …
Adversarial attacks on multi-focus image fusion models
Multi-focus image fusion aims to create an all-in-focus clear image by fusing a set of partially
focused images. In recent years, various multi-focus image fusion methods based on deep …
focused images. In recent years, various multi-focus image fusion methods based on deep …
MFIF-GAN: A new generative adversarial network for multi-focus image fusion
Abstract Multi-Focus Image Fusion (MFIF) is a promising image enhancement technique to
generate all-in-focus images meeting visual needs, and it is a precondition for other …
generate all-in-focus images meeting visual needs, and it is a precondition for other …