{"title":"基于线性结构张量的像素级图像融合","authors":"B. Lu, Chunli Miao, Hui Wang","doi":"10.1109/YCICT.2010.5713105","DOIUrl":null,"url":null,"abstract":"A pixel-level image fusion method based on linear structure tensor is proposed within wavelet framework. Structure tensor, which describes local structure information with its eigenvalues and eigenvectors, is adopted to design a feature selection algorithm to reconstruct high-frequency wavelet coefficients of fused image. Experimental results on grayscale and color images show that the linear structure tensor based fusion scheme can preserve more details.","PeriodicalId":179847,"journal":{"name":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Pixel level image fusion based on linear structure tensor\",\"authors\":\"B. Lu, Chunli Miao, Hui Wang\",\"doi\":\"10.1109/YCICT.2010.5713105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A pixel-level image fusion method based on linear structure tensor is proposed within wavelet framework. Structure tensor, which describes local structure information with its eigenvalues and eigenvectors, is adopted to design a feature selection algorithm to reconstruct high-frequency wavelet coefficients of fused image. Experimental results on grayscale and color images show that the linear structure tensor based fusion scheme can preserve more details.\",\"PeriodicalId\":179847,\"journal\":{\"name\":\"2010 IEEE Youth Conference on Information, Computing and Telecommunications\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Youth Conference on Information, Computing and Telecommunications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YCICT.2010.5713105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YCICT.2010.5713105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pixel level image fusion based on linear structure tensor
A pixel-level image fusion method based on linear structure tensor is proposed within wavelet framework. Structure tensor, which describes local structure information with its eigenvalues and eigenvectors, is adopted to design a feature selection algorithm to reconstruct high-frequency wavelet coefficients of fused image. Experimental results on grayscale and color images show that the linear structure tensor based fusion scheme can preserve more details.
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