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To preserve more useful information from source images, the new fusion rules are developed to combine the subbands with the varied frequencies. That is, the low frequency subbands are fused by utilizing two activity measures based on the regional standard deviation and Shannon entropy and the high frequency subbands are merged together via weight maps which are determined by the saliency values of pixels. The experimental results demonstrate that the proposed method significantly outperforms the conventional NSCT based medical image fusion approaches in both visual perception and evaluation indices.<\/jats:p>","DOI":"10.1155\/2015\/262819","type":"journal-article","created":{"date-parts":[[2015,10,8]],"date-time":"2015-10-08T00:49:01Z","timestamp":1444265341000},"page":"1-13","source":"Crossref","is-referenced-by-count":6,"title":["The Nonsubsampled Contourlet Transform Based Statistical Medical Image Fusion Using Generalized Gaussian Density"],"prefix":"10.1155","volume":"2015","author":[{"given":"Guocheng","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Department of Biomedical Engineering, Sichuan Medical University, Zhongshan Road, Luzhou, Sichuan 646000, China"},{"name":"Provincial Key Laboratory of Digital Media, Chengdu 611731, 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