Infrared and visible image fusion using Latent Low-Rank Representation

Hui Li, Xiao-Jun Wu*
Infrared and visible image fusion using Latent Low-Rank Representation.
arXiv

Latent Low-Rank Representation

The framework for fusion method

Abstract

We propose a novel image fusion method based on latent low-rank representation (LatLRR) which is simple and effective.

Firstly, the source images are decomposed into low-rank part and saliency part by LatLRR. The global structure information is preserved by low-rank part, and the local structure information is extracted by saliency part.

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.

Source code

1 fusion_latlrr.m ----- our method

2 latlent_lrr.m ------- latent low-rank representation method

Latent LRR

The Latent LRR method is proposed by Guangcan Liu in 2011.

"Liu G, Yan S. Latent Low-Rank Representation for subspace segmentation and feature extraction[C] International Conference on Computer Vision. IEEE Computer Society, 2011:1615-1622."

And we just use this method in our paper without change.

Citation

For codes:

@misc{li2017IVimagefusion_latentLRR,
    author = {Hui Li},
    title = {CODE: Infrared and visible image fusion using Latent Low-Rank Representation},
    year = {2017},
    note = {\url{https://github.com/exceptionLi/imagefusion_Infrared_visible_latlrr}}
  }