arXiv 1804.089922018-04cs.CV

基于潜在低秩表示的红外与可见光图像融合

Infrared and visible image fusion using Latent Low-Rank Representation

Jiangnan University（江南大学）

Hui Li, Xiao-Jun Wu

备注：: 6 pages, 8 figures, 1 tables

摘要：

红外与可见光图像融合是图像融合领域的一个重要课题，在许多领域有着广泛的应用。为了更好地保留源图像中的有用信息，提出了一种简单有效的基于潜在低秩表示（LatLRR）的图像融合方法。首先，利用LatLRR将源图像分解为低秩部分（全局结构）和显著部分（局部结构）。然后对低秩部分采用加权平均策略进行融合，以保留更多的轮廓信息。然后，简单的突出部分融合的求和策略，这是一个有效的操作，在该融合框架。最后，将融合后的低秩部分和显著部分进行融合，得到融合图像。实验结果表明，该方法在主观和客观评价上均优于现有的融合方法。我们的融合方法的代码可以在https：//github.com/hli1221/imagefusion\_Infrared\_visible\_latlrr上找到

英文摘要：

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. Firstly, the source images are decomposed into low-rank parts(global structure) and salient parts(local structure) by LatLRR. Then, the low-rank parts are fused by weighted-average strategy to preserve more contour information. Then, the salient parts are simply fused by sum strategy which is a efficient operation in this fusion framework. Finally, the fused image is obtained by combining the fused low-rank part and the fused salient 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/hli1221/imagefusion\_Infrared\_visible\_latlrr

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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