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 …
A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics
Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
SwinFusion: Cross-domain long-range learning for general image fusion via swin transformer
This study proposes a novel general image fusion framework based on cross-domain long-
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …
Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network
Infrared and visible image fusion aims to synthesize a single fused image that not only
contains salient targets and abundant texture details but also facilitates high-level vision …
contains salient targets and abundant texture details but also facilitates high-level vision …
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …
death cases and affected all sectors of human life. With gradual progression of time, COVID …
MATR: Multimodal medical image fusion via multiscale adaptive transformer
Owing to the limitations of imaging sensors, it is challenging to obtain a medical image that
simultaneously contains functional metabolic information and structural tissue details …
simultaneously contains functional metabolic information and structural tissue details …
GANMcC: A generative adversarial network with multiclassification constraints for infrared and visible image fusion
Visible images contain rich texture information, whereas infrared images have significant
contrast. It is advantageous to combine these two kinds of information into a single image so …
contrast. It is advantageous to combine these two kinds of information into a single image so …
IFCNN: A general image fusion framework based on convolutional neural network
In this paper, we propose a general image fusion framework based on the convolutional
neural network, named as IFCNN. Inspired by the transform-domain image fusion …
neural network, named as IFCNN. Inspired by the transform-domain image fusion …
Pan-GAN: An unsupervised pan-sharpening method for remote sensing image fusion
Pan-sharpening in remote sensing image fusion refers to obtaining multi-spectral images of
high-resolution by fusing panchromatic images and multi-spectral images of low-resolution …
high-resolution by fusing panchromatic images and multi-spectral images of low-resolution …
YDTR: Infrared and visible image fusion via Y-shape dynamic transformer
Infrared and visible image fusion is aims to generate a composite image that can
simultaneously describe the salient target in the infrared image and texture details in the …
simultaneously describe the salient target in the infrared image and texture details in the …