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

Li, Hui, Wu, Xiao-Jun and Kittler, Josef (2020) MDLatLRR: A novel decomposition method for infrared and visible image fusion IEEE Transactions on Image Processing, 29.

MDLatLRR-TIP2020.pdf - Accepted version Manuscript

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Image decomposition is crucial for many image processing tasks, as it allows to extract salient features from source images. A good image decomposition method could lead to a better performance, especially in image fusion tasks. We propose a multi-level image decomposition method based on latent lowrank representation(LatLRR), which is called MDLatLRR. This decomposition method is applicable to many image processing fields. In this paper, we focus on the image fusion task. We build a novel image fusion framework based on MDLatLRR which is used to decompose source images into detail parts(salient features) and base parts. A nuclear-norm based fusion strategy is used to fuse the detail parts and the base parts are fused by an averaging strategy. Compared with other state-of-the-art fusion methods, the proposed algorithm exhibits better fusion performance in both subjective and objective evaluation.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Wu, Xiao-Jun
Date : 28 February 2020
DOI : 10.1109/TIP.2020.2975984
OA Location :
Copyright Disclaimer : Copyright © 2020, IEEE
Depositing User : James Marshall
Date Deposited : 10 Jul 2020 10:06
Last Modified : 10 Jul 2020 10:06

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