Infrared and visible image fusion using a novel deep decomposition method
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Infrared and visible image fusion is an important problem in image fusion tasks which has been applied widely in many fields. To better preserve the useful information from source images, in this paper, we propose an effective image fusion framework using a novel deep decomposition method which based on Latent Low-Rank Representation(LatLRR). And this decomposition method is also named DDLatLRR. Firstly, the LatLRR is utilized to learn a project matrix which used to extract salient features. Then, the base part and multi-level detail parts are obtained by DDLatLRR. With adaptive fusion strategies, the fused base part and the fused detail parts are reconstructed. Finally, the fused image is obtained by combine the fused base part and the detail parts. Compared with other fusion methods experimentally, the proposed algorithm has better fusion performance than state-of-the-art fusion methods in both subjective and objective evaluation. The Code of our fusion method is available at https://github.com/exceptionLi/imagefusion_deepdecomposition
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