计算机应用与软件Issue(3)：203-206,245,5.DOI:10.3969/j.issn.1000-386x.2014.03.053
基于稀疏表示的自适应图像融合方法研究
STUDY ON SPARSE REPRESENTATION BASED ADAPTIVE IMAGE FUSION METHODS
摘要
Abstract
Image fusion means combining two or more images or image sequence information about one particular scene taken by different sensors either simultaneously or unsimultaneously,so that the fused image is more analyzable and comprehensible.On the basis of present classical image fusion methods,the paper proposes a new sparse representation based adaptive image fusion algorithm.The method firstly presents two source images as two groups of sparse coefficients by trained over-completed dictionary;then according to coefficient characteristics adaptively chooses fusion rules to fuse coefficients;finally reconstructs fused coefficients and dictionary to obtain the fused image.During sparse representation process the algorithm can effectively avoid the generation of block-effect and can eliminate noises;therefore the image quality is improved.Experimental results show that the proposed method is superior to the other algorithms either at subjective or objective evaluations.关键词
稀疏表示/图像融合/超完备字典/自适应Key words
Sparse representation/Image fusion/Over-completed dictionary/Adaptive分类
信息技术与安全科学引用本文复制引用
肖冬杰,李其申,周翠岭..基于稀疏表示的自适应图像融合方法研究[J].计算机应用与软件,2014,(3):203-206,245,5.基金项目
航空科技重点实验室开放基金项目（ZK201029002）；南昌航空大学研究生创新基金项目（YC2011042）。 （）
