A lightweight pixel-level unified image fusion network
In recent years, deep-learning-based pixel-level unified image fusion methods have
received more and more attention due to their practicality and robustness. However, they …
received more and more attention due to their practicality and robustness. However, they …
Detail-aware near infrared and visible fusion with multi-order hyper-Laplacian priors
Heavy haze/noise can cause unpleasant information loss in near infrared (NIR) and visible
(VI) image fusion. To generate high-quality fused images, this paper proposes a detail …
(VI) image fusion. To generate high-quality fused images, this paper proposes a detail …
F-DARTS: Foveated differentiable architecture search based multimodal medical image fusion
S Ye, T Wang, M Ding, X Zhang - IEEE Transactions on Medical …, 2023 - ieeexplore.ieee.org
Multimodal medical image fusion (MMIF) is highly significant in such fields as disease
diagnosis and treatment. The traditional MMIF methods are difficult to provide satisfactory …
diagnosis and treatment. The traditional MMIF methods are difficult to provide satisfactory …
Denoiser Learning for Infrared and Visible Image Fusion
Infrared image (IR) and visible image (VI) fusion creates fusion images that contain richer
information and gain improved visual effects. Existing methods generally use the operators …
information and gain improved visual effects. Existing methods generally use the operators …
Near-infrared and visible fusion for image enhancement based on multi-scale decomposition with rolling WLSF
Y Zhu, X Sun, H Zhang, J Wang, X Fu - Infrared Physics & Technology, 2023 - Elsevier
Generally, the visible (VIS) image (RGB image is used here) captured by the VIS band
sensor is often blurred by the influence of haze, strong light, or dark environment. However …
sensor is often blurred by the influence of haze, strong light, or dark environment. However …
Convolutional simultaneous sparse approximation with applications to RGB-NIR image fusion
Simultaneous sparse approximation (SSA) seeks to represent a set of dependent signals
using sparse vectors with identical supports. The SSA model has been used in various …
using sparse vectors with identical supports. The SSA model has been used in various …
Noisy and non-stationary power quality disturbance classification based on adaptive segmentation empirical wavelet transform and support vector machine
The empirical wavelet transform (EWT) has demonstrated better performance in signal noise
removal compared to other threshold techniques based on the conventional wavelet …
removal compared to other threshold techniques based on the conventional wavelet …
LRINet: Long-range imaging using multispectral fusion of RGB and NIR images
L Liu, F Wang, C Jung - Information Fusion, 2023 - Elsevier
When imaging at a long distance by ordinary visible cameras, the wavelength of visible light
is easily interfered by fog or atmospheric effects, resulting in blurry or lost details in RGB …
is easily interfered by fog or atmospheric effects, resulting in blurry or lost details in RGB …
Visible and NIR image fusion based on multiscale gradient guided edge-smoothing model and local gradient weight
D Zou, B Yang, Y Li, X Zhang, L Pang - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The visible (VS) and near-infrared (NIR) image fusion is a common approach to improve
image visibility, which saves rich scene details and similar colors to the VS image in fused …
image visibility, which saves rich scene details and similar colors to the VS image in fused …
A novel approach to low-light image and video enhancement using adaptive dual super-resolution generative adversarial networks and top-hat filtering
S Rani - Computers and Electrical Engineering, 2025 - Elsevier
Image and video enhancement under low-light conditions is challenging, as the task
involves more than just brightness adjustment. Without addressing issues such as artifacts …
involves more than just brightness adjustment. Without addressing issues such as artifacts …