中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
General fusion method for infrared and visual images via latent low-rank representation and local non-subsampled shearlet transform

文献类型:期刊论文

作者Cheng, B. Y.; Jin, L. X.; Li, G. N.
刊名Infrared Physics & Technology
出版日期2018
卷号92页码:68-77
关键词Latent low-rank representation Local non-subsampled shearlet transform Salient features Image fusion visible-light contourlet transform feature-extraction nsct domain algorithm pcnn nsst Instruments & Instrumentation Optics Physics
ISSN号1350-4495
DOI10.1016/j.infrared.2018.05.006
英文摘要This study establishes the general fusion method for infrared and visual images via latent low-rank representation (LatLRR) and local non-sampled shearlet transform (LNSST) to effectively combine the salient information of both images and solve problems on low-contrasting heterogeneous image fusion. First, LNSST is used as a multi-scale analysis tool to decompose the source images into low-pass and high-pass sub-images. Second, the LatLRR, which is an effective method for exploring multiple subspace structural data, is used to extract the salient information of image sources. Thus, the LatLRR can be adopted to guide the adaptive weighted fusion of low-pass sub-images. Simultaneously, the average gradient, which can reflect image edge details, is regarded as the fusion rule for high-pass sub-images. A series of images from diverse scenes are used for the fusion experiments, and the results are evaluated subjectively and objectively. The subjective and objective evaluations show that our algorithm exhibited superior visual performance, and the values of the objective evaluation parameters increase by about 5-10% compared with other typical fusion methods.
源URL[http://ir.ciomp.ac.cn/handle/181722/61002]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714
Cheng, B. Y.,Jin, L. X.,Li, G. N.. General fusion method for infrared and visual images via latent low-rank representation and local non-subsampled shearlet transform[J]. Infrared Physics & Technology,2018,92:68-77.
APA Cheng, B. Y.,Jin, L. X.,&Li, G. N..(2018).General fusion method for infrared and visual images via latent low-rank representation and local non-subsampled shearlet transform.Infrared Physics & Technology,92,68-77.
MLA Cheng, B. Y.,et al."General fusion method for infrared and visual images via latent low-rank representation and local non-subsampled shearlet transform".Infrared Physics & Technology 92(2018):68-77.

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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