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arXiv · 1811.02291

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

Hui Li·Xiao-Jun Wu·Josef Kittler
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Abstract

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 low-rank 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 develop 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.

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Hui Li, Xiao-Jun Wu, Josef Kittler. 2018-11-06. MDLatLRR: A novel decomposition method for infrared and visible image fusion. https://doi.org/10.1109/tip.2020.2975984

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