广西科技大学学报2016，Vol.27Issue(4)：15-20,6.DOI:10.16375/j.cnki.cn45-1395/t.2016.04.003
基于邻域能量的压缩感知医学图像融合研究
Medical image fusion based on compressed sensing and local energy
摘要
Abstract
Multi-model medical image fusion can greatly enrich the image information and improve the diagnosis of clinical medicine. In this paper, along with the theory of compressed sensing, we take Contourlet transform for the decomposition of original images to get the low frequency part and high frequency part; the low frequency sub-bands is fused by using a weighted average approach, and the high-frequency sub-bands with high noise content is fused by using weighted local energy fusion rule. Through medical image simulation, the algorithm can increase the multi-modal medical image complementary information, and can improve the clarity of medical images fusion. The fusion evaluations confirm that the algorithm has good results in terms of subjective and objective evaluation.关键词
医学图像融合/Contourlet变换/压缩感知/邻域能量Key words
medical image fusion/Contourlet transform/compressed sensing/local energy分类
信息技术与安全科学引用本文复制引用
李春贵,陶佳伟,周爱霞..基于邻域能量的压缩感知医学图像融合研究[J].广西科技大学学报,2016,27(4):15-20,6.基金项目
国家自然科学基金项目（61302178）资助 （）
