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 …
Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in developing new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
SDNet: A versatile squeeze-and-decomposition network for real-time image fusion
In this paper, a squeeze-and-decomposition network (SDNet) is proposed to realize multi-
modal and digital photography image fusion in real time. Firstly, we generally transform …
modal and digital photography image fusion in real time. Firstly, we generally transform …
A review of multimodal image matching: Methods and applications
Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …
similar structure/content from two or more images that are of significant modalities or …
[HTML][HTML] A review on deep learning in UAV remote sensing
Abstract Deep Neural Networks (DNNs) learn representation from data with an impressive
capability, and brought important breakthroughs for processing images, time-series, natural …
capability, and brought important breakthroughs for processing images, time-series, natural …
A multiscale framework with unsupervised learning for remote sensing image registration
Registration for multisensor or multimodal image pairs with a large degree of distortions is a
fundamental task for many remote sensing applications. To achieve accurate and low-cost …
fundamental task for many remote sensing applications. To achieve accurate and low-cost …
SACF-Net: Skip-attention based correspondence filtering network for point cloud registration
Rigid registration is a transformation estimation problem between two point clouds. The two
point clouds captured may partially overlap owing to different viewpoints and acquisition …
point clouds captured may partially overlap owing to different viewpoints and acquisition …
Silk: Simple learned keypoints
Keypoint detection & descriptors are foundational technologies for computer vision tasks like
image matching, 3D reconstruction and visual odometry. Hand-engineered methods like …
image matching, 3D reconstruction and visual odometry. Hand-engineered methods like …
Murf: Mutually reinforcing multi-modal image registration and fusion
Existing image fusion methods are typically limited to aligned source images and have to
“tolerate” parallaxes when images are unaligned. Simultaneously, the large variances …
“tolerate” parallaxes when images are unaligned. Simultaneously, the large variances …
R₂FD₂: fast and robust matching of multimodal remote sensing images via repeatable feature detector and rotation-invariant feature descriptor
B Zhu, C Yang, J Dai, J Fan, Y Qin… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Identifying feature correspondences between multimodal images is facing enormous
challenges because of the significant differences both in radiation and geometry. To address …
challenges because of the significant differences both in radiation and geometry. To address …