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Title: Multi-focus image fusion based on adaptive dual-channel spiking cortical model in non-subsampled shearlet domain
Authors: Liu, SQ
Wang, J
Lu, YC
Li, HL 
Zhao, J
Zhu, ZH
Keywords: Difference images
Multi-focus image fusion
Non-subsampled shearlet
Spiking cortical model
Issue Date: 2019
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE access, 2019, v. 7, p. 56367-56388 How to cite?
Journal: IEEE access 
Abstract: To get a better fused performance in the multi-focus image fusion based on a transform domain, a new multi-focus image algorithm combined with the adaptive dual-channel spiking cortical model (SCM) in non-subsampled shearlet (NSST) domain and the difference images is proposed in this paper. First, a basic fused image is constructed in the NSST domain by registering the source image and adaptive dual channel SCM (dual-channel SCM). Next, the focus areas of the sources input images based on the difference images between the basic fused image and the sources images are detected. In the end, the final fused image generated in this paper is realized by combining the focal regions. Because of the global coupling of the dual-SCM, the synchronization characteristics of the pulse, and the multi-resolution and direction of the NSST, the proposed algorithm can preserve the information of the source's image well and present a clear image more in line with the human visual effects. In summary, the image fusion algorithm that we have designed is superior to the most advanced algorithms.
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2900376
Rights: © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information.
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The following publication S. Liu, J. Wang, Y. Lu, H. Li, J. Zhao and Z. Zhu, "Multi-Focus Image Fusion Based on Adaptive Dual-Channel Spiking Cortical Model in Non-Subsampled Shearlet Domain," in IEEE Access, vol. 7, pp. 56367-56388, 2019 is available at
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