Foteini Agrafioti, Jiexin Gao, H. Mohammadzade, D. Hatzinakos
{"title":"A 2D bivariate EMD algorithm for image fusion","authors":"Foteini Agrafioti, Jiexin Gao, H. Mohammadzade, D. Hatzinakos","doi":"10.1109/ICDSP.2011.6004923","DOIUrl":null,"url":null,"abstract":"Although the benefits of the empirical mode decomposition, in analyzing stochastic signals have been reported, and the algorithm has been established for fusion applications, there is currently no solution to the problem of the simultaneous decomposition of 2D data. This paper proposes an extension of the bivariate EMD (BEMD) [1] algorithm for 2D sources, which retains spatial information while addressing the uniqueness problem of the intrinsic mode functions. The performance of the algorithm is tested on partially blurred and defocused images. The fused images are compared against 1D-BEMD solutions, to demonstrate increased visual quality of the result.","PeriodicalId":360702,"journal":{"name":"2011 17th International Conference on Digital Signal Processing (DSP)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 17th International Conference on Digital Signal Processing (DSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2011.6004923","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Although the benefits of the empirical mode decomposition, in analyzing stochastic signals have been reported, and the algorithm has been established for fusion applications, there is currently no solution to the problem of the simultaneous decomposition of 2D data. This paper proposes an extension of the bivariate EMD (BEMD) [1] algorithm for 2D sources, which retains spatial information while addressing the uniqueness problem of the intrinsic mode functions. The performance of the algorithm is tested on partially blurred and defocused images. The fused images are compared against 1D-BEMD solutions, to demonstrate increased visual quality of the result.