Infrared and visible image fusion using Latent Low-Rank Representation
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Infrared and visible image fusion is an important problem in the field of image fusion which has been applied widely in many fields. To better preserve the useful information from source images, in this paper, we propose a novel image fusion method based on latent low-rank representation(LatLRR) which is simple and effective. This is the first time that LatLRR is introduced to image fusion. Firstly, the source images are decomposed into low-rank parts(global structure) and saliency parts(local structure) by LatLRR. Then, the low-rank parts are fused by weighted-average strategy, and the saliency parts are simply fused by sum strategy. Finally, the fused image is obtained by combining the fused low-rank part and the fused saliency part. Compared with other fusion methods experimentally, the proposed method 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_Infrared_visible_latlrr
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