Journal
INFRARED PHYSICS & TECHNOLOGY
Volume 76, Issue -, Pages 174-184Publisher
ELSEVIER
DOI: 10.1016/j.infrared.2016.02.005
Keywords
Image fusion; Low-level features; Activity measure; Multi-scale transform
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Funding
- National Natural Science Foundation of China [61302041, 61562053]
- Applied Basic Research Foundation of Yunnan Provincial Science and Technology Department [2013FD011]
- Talent Cultivation Foundation of Kunming University of Science and Technology [KKZ3201 303027]
- Yunnan Provincial for Personnel Cultivation [KKSY201303086, KKSY201403116]
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Multi-scale transform (MST) is an efficient tool for image fusion. Recently, many fusion methods have been developed based on different MSTs, and they have shown potential application in many fields. In this paper, we propose an effective infrared and visible image fusion scheme in nonsubsampled contourlet transform (NSCT) domain, in which the NSCT is firstly employed to decompose each of the source images into a series of high frequency subbands and one low frequency subband. To improve the fusion performance we designed two new activity measures for fusion of the lowpass subbands and the high-pass subbands. These measures are developed based on the fact that the human visual system (HVS) percept the image quality mainly according to its some low-level features. Then, the selection principles of different subbands are presented based on the corresponding activity measures. Finally, the merged sub bands are constructed according to the selection principles, and the final fused image is produced by applying the inverse NSCT on these merged subbands. Experimental results demonstrate the effectiveness and superiority of the proposed method over the state-of-the-art fusion methods in terms of both visual effect and objective evaluation results. (C) 2016 Elsevier B.V. All rights reserved.
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