Infrared And Visible Image Fusion

28 papers with code • 0 benchmarks • 4 datasets

Image fusion with paired infrared and visible images

Most implemented papers

Infrared and Visible Image Fusion with ResNet and zero-phase component analysis

exceptionLi/imagefusion_resnet50 19 Jun 2018

Feature extraction and processing tasks play a key role in Image Fusion, and the fusion performance is directly affected by the different features and processing methods undertaken.

Infrared and visible image fusion using Latent Low-Rank Representation

exceptionLi/imagefusion_Infrared_visible_latlrr 24 Apr 2018

Then, the low-rank parts are fused by weighted-average strategy to preserve more contour information.

MDLatLRR: A novel decomposition method for infrared and visible image fusion

exceptionLi/imagefusion_deepdecomposition 6 Nov 2018

We develop a novel image fusion framework based on MDLatLRR, which is used to decompose source images into detail parts(salient features) and base parts.

DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion

Zhaozixiang1228/IVIF-DIDFuse 20 Mar 2020

Infrared and visible image fusion, a hot topic in the field of image processing, aims at obtaining fused images keeping the advantages of source images.

Bayesian Fusion for Infrared and Visible Images

Zhaozixiang1228/Bayesian-Fusion 12 May 2020

In this paper, a novel Bayesian fusion model is established for infrared and visible images.

Deep Convolutional Sparse Coding Networks for Image Fusion

xsxjtu/CSC-MEFN 18 May 2020

Image fusion is a significant problem in many fields including digital photography, computational imaging and remote sensing, to name but a few.

A Dual-branch Network for Infrared and Visible Image Fusion

thfylsty/ICPR2020_A_Dual_branch_Network_for_Infrared_and_Visible_Image_Fusion 24 Jan 2021

Deep learning is a rapidly developing approach in the field of infrared and visible image fusion.

PIAFusion: A progressive infrared and visible image fusion network based on illumination aware

Linfeng-Tang/PIAFusion Information Fusion 2022

Moreover, we utilize the illumination probability to construct an illumination-aware loss to guide the training of the fusion network.

Fusing Multiple Multiband Images

Reza219/Multiple-multiband-image-fusion 13 Dec 2017

We use the well-known forward observation and linear mixture models with Gaussian perturbations to formulate the maximum-likelihood estimator of the endmember abundance matrix of the fused image.