软件导刊2017，Vol.16Issue(3)：163-166,4.DOI:10.11907/rjdk.162607
基于高阶奇异值分解的多聚焦图像融合新方法
A New Multi-focus Image Fusion Method Based on Higher Order Singular Value Decomposition
摘要
Abstract
For the problem of traditional multi-focus image fusion methods can not effectively measure the focus regions in images,a new multi-focus image fusion method is proposed based on higher order singular value decomposition.As higher order singular value decomposition (HOSVD) can exactly extract features in images,HOSVD is used as an effective decomposition tool.Considering the regional correlation between pixels,space frequency,average gradient and regional energy are extracted.And a novel fusion strategy on comprehensive consideration of multiple regional features is applied to decomposition coefficients.Experimental results show that the proposed method performs better than traditional image fusion methods.关键词
图像融合/多聚焦图像/高阶奇异值分解/空间频率/平均梯度/区域能量Key words
Image Fusion/Multi-focus Image/Higher Order Singular Value Decomposition/Space Frequency/Average Gradient/Regional Energy分类
信息技术与安全科学引用本文复制引用
张翠英,高瑞超..基于高阶奇异值分解的多聚焦图像融合新方法[J].软件导刊,2017,16(3):163-166,4.基金项目
中国博士后科学基金项目(2013M541601) （2013M541601）
