文章基本信息

标题：An Image Fusion Method Based on NSCT and Dual-channel PCNN Model
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作者：Wang, Nianyi ; Ma, Yide ; Wang, Weilan 等
期刊名称：Journal of Networks
印刷版ISSN：1796-2056
出版年度：2014
卷号：9
期号：2
页码：501-506
DOI：10.4304/jnw.9.2.501-506
语种：English
出版社：Academy Publisher
摘要：NSCT is one of useful multiscale geometric analysis tools, which takes full advantage of geometric regularity of image intrinsic structures. The dual-channel PCNN is a simplified PCNN model, which can process multiple images by a single PCNN. This saves time in the process of image fusion and cuts down computational complexity. In this paper, we present a new image fusion scheme based on NSCT and dual-channel PCNN. Firstly, the fusion rules of subband coefficients of NSCT are discussed. For the fusion rule of low frequency coefficients, the maximum selection rule (MSR) is used. Then, for the fusion rule of high frequency coefficients, spatial frequency (SF) of each high frequency subband is considered as the gradient features of images to motivate dual-channel PCNN networks and generate pulse of neurons. At last, fused image is obtained by using the inverse NSCT transform. In order to show that the proposed method can deal with image fusion, we used two pairs of images as our experimental subjects. The proposed method is compared with other five methods. The performance of various methods is mathematically evaluated by using four image quality evaluation criteria. Experimental comparisons conducted on different fusion methods prove the effectiveness of the proposed fusion method
关键词：Image Fusion;Nonsubsampled Contourlet Transform (NSCT);Pulse Coupled Neural Network (PCNN);Dual-Channel PCNN;Spatial Frequency