Infrared and visual image fusion using LNSST and an adaptive dual-channel PCNN with triple-linking strength

doi:10.1016/j.neucom.2018.05.028

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	Infrared and visual image fusion using LNSST and an adaptive dual-channel PCNN with triple-linking strength
	Cheng, B. Y.; Jin, L. X.; Li, G. N.
	2018
发表期刊	Neurocomputing
ISSN	0925-2312
卷号	310 页码:135-147
摘要	This paper presents a novel fusion framework for infrared and visual image that uses an adaptive dual-channel pulse-coupled neural network (PCNN) with triple-linking strength (ATD-PCNN) in a local non-subsampled shearlet transform (LNSST) domain. First, the LNSST, which is an upgrade based on the NSST, is used as a multi-scale analysis tool to decompose the source images into low-pass and high-pass sub-images. Second, an improved sum-modified Laplacian (ISML) that reflects the energy characteristics of low-pass sub-images in the LNSST domain is used to stimulate the ATD-PCNN model, and an improved average gradient (IAVG) that reflects the textural details of high-pass sub-images is used to stimulate the ATD-PCNN neurons. Furthermore, to solve the problem of the spectral difference between infrared and visible light, three novel operators are used as the adaptive linking strength, and an optimization model based on l(2)-norm is used for merging the output coefficients. A series of images from diverse scenes are used for the fusion experiments, and the fusion results are evaluated subjectively and objectively. The results of the subjective and objective evaluations show that our algorithm exhibits superior fusion performance and is more effective than typical fusion techniques. (C) 2018 Elsevier B.V. All rights reserved.
关键词	LNSST ATD-PCNN Image fusion Singular value decomposition Auxiliary linking strength Triple-linking strength sparse representation shearlet transform multi-focus feature-extraction neural-network domain algorithm decomposition Computer Science
DOI	10.1016/j.neucom.2018.05.028
收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/61036
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.. Infrared and visual image fusion using LNSST and an adaptive dual-channel PCNN with triple-linking strength[J]. Neurocomputing,2018,310:135-147.
APA	Cheng, B. Y.,Jin, L. X.,&Li, G. N..(2018).Infrared and visual image fusion using LNSST and an adaptive dual-channel PCNN with triple-linking strength.Neurocomputing,310,135-147.
MLA	Cheng, B. Y.,et al."Infrared and visual image fusion using LNSST and an adaptive dual-channel PCNN with triple-linking strength".Neurocomputing 310(2018):135-147.

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