TCCFusion: An infrared and visible image fusion method based on transformer and cross correlation
Infrared and visible image fusion aims to obtain a synthetic image that can simultaneously
exhibit salient objects and provide abundant texture details. However, existing deep …
exhibit salient objects and provide abundant texture details. However, existing deep …
Dm-fusion: Deep model-driven network for heterogeneous image fusion
Heterogeneous image fusion (HIF) is an enhancement technique for highlighting the
discriminative information and textural detail from heterogeneous source images. Although …
discriminative information and textural detail from heterogeneous source images. Although …
On and beyond total variation regularization in imaging: the role of space variance
Over the last 30 years a plethora of variational regularization models for image
reconstruction have been proposed and thoroughly inspected by the applied mathematics …
reconstruction have been proposed and thoroughly inspected by the applied mathematics …
A fast and accurate small target detection algorithm based on feature fusion and cross-layer connection network for the SAR images
M Sun, Y Li, X Chen, Y Zhou, J Niu… - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Target detection technology has been greatly improved for synthetic aperture radar (SAR)
images recently, due to the advancement in the deep learning domain. However, because of …
images recently, due to the advancement in the deep learning domain. However, because of …
Multi-image fusion: optimal decomposition strategy with heuristic-assisted non-subsampled shearlet transform for multimodal image fusion
Image fusion is significant in various distinct sectors of image processing, from remote
sensing to medical applications. In recent years, real-valued wavelet transforms have been …
sensing to medical applications. In recent years, real-valued wavelet transforms have been …
A nonlocal method for image shadow removal
S Benalia, M Hachama - Computers & Mathematics with Applications, 2022 - Elsevier
This paper proposes a new model for image shadow removal. The model reformulates a
recent osmosis model with nonlocal differential operators. This allows to benefit from distant …
recent osmosis model with nonlocal differential operators. This allows to benefit from distant …
A multi‐focus image fusion method based on multi‐source joint layering and convolutional sparse representation
Y Hu, Z Chen, B Zhang, L Ma, J Li - IET Image Processing, 2022 - Wiley Online Library
In this paper, a new Multi‐Focus Image Fusion (MFIF) method based on multi‐source joint
layering and Convolutional Sparse Representation (CSR) is proposed. Based on the …
layering and Convolutional Sparse Representation (CSR) is proposed. Based on the …
A method of image stitching with partition matching and direct detection for rotated image
Z Qu, J Li, L Gao - Displays, 2022 - Elsevier
Aiming at the problem of stitching overlapped images taken under different rotation angles,
we present an effective and adaptive method to rotate the image to an appropriate angle …
we present an effective and adaptive method to rotate the image to an appropriate angle …
Generalised scale-space properties for probabilistic diffusion models
P Peter - International Conference on Scale Space and …, 2023 - Springer
Probabilistic diffusion models enjoy increasing popularity in the deep learning community.
They generate convincing samples from a learned distribution of input images with a wide …
They generate convincing samples from a learned distribution of input images with a wide …
Generalised Diffusion Probabilistic Scale-Spaces
P Peter - Journal of Mathematical Imaging and Vision, 2024 - Springer
Diffusion probabilistic models excel at sampling new images from learned distributions.
Originally motivated by drift-diffusion concepts from physics, they apply image perturbations …
Originally motivated by drift-diffusion concepts from physics, they apply image perturbations …