General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural Networks

General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural Networks

In this paper, we propose a unified and flexible framework for general image fusion tasks, including multi-exposure image fusion, multi-focus image fusion, infrared/visible image fusion, and multi-modality medical image fusion. Unlike other deep learning-based image fusion methods applied to a fixed...

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Bibliographic Details
Main Authors: Yifan Xiao, Zhixin Guo, Peter Veelaert, Wilfried Philips
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Sensors
Subjects:
image fusion
multiple inputs
permutation-invariant network
continual learning
Online Access:https://www.mdpi.com/1424-8220/22/7/2457

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