文章基本信息

标题：Adaptive Technique for Image Fusion based on Non-Subsampled Shearlet Transform-Spatial Frequency-Human Visual Factor
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作者：NIU Ling ; FENG Gao-feng
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：3
页码：457-466
DOI：10.14257/ijsip.2016.9.3.39
出版社：SERSC
摘要：As a novel multi-scale geometrical analysis theory, non-subsampled shearlet transform (NSST) own much better competences of image processing. An adaptive technique for image fusion based on NSST-spatial frequency (SF)-human visual factor (HVF) is proposed in this paper. Each source image can be converted into corresponding multi-scale and multi-directional frameworks via NSST. SF and HVF are utilized to conduct the fusion courses of low-frequency and high-frequency sub images, respectively. Besides, an adaptive fusion algorithm based on NSST is devised. Finally, the final fused image can be obtained by using inverse NSST. Simulation experimental demonstrates that, compared with other classic techniques, the proposed technique has much better performance in terms of visual performance and information capturing.
关键词：non-subsampled shearlet transform; spatial frequency; human visual factor; ; adaptive