{"title":"基于非负矩阵分解的图像融合","authors":"Junying Zhang, Le Wei, Q. Miao, Y. Wang","doi":"10.1109/ICIP.2004.1419463","DOIUrl":null,"url":null,"abstract":"Nonnegative Matrix Factorization technique (NMF) has been shown to have various applications to image processing, because of its power of local or part-based representation of objects and/or images. In this paper, we present an image fusion method based on NMF, not by the part-based representation feature of NMF, but by its wholly representation of the images needed to be fused: the images are fused by NMF with the parameter r of the NMF to be set to 1. Our experimental results show that the proposed method is efficient and effective for image fusion compared with many other image fusion methods.","PeriodicalId":184798,"journal":{"name":"2004 International Conference on Image Processing, 2004. ICIP '04.","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Image fusion based on nonnegative matrix factorization\",\"authors\":\"Junying Zhang, Le Wei, Q. Miao, Y. Wang\",\"doi\":\"10.1109/ICIP.2004.1419463\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nonnegative Matrix Factorization technique (NMF) has been shown to have various applications to image processing, because of its power of local or part-based representation of objects and/or images. In this paper, we present an image fusion method based on NMF, not by the part-based representation feature of NMF, but by its wholly representation of the images needed to be fused: the images are fused by NMF with the parameter r of the NMF to be set to 1. Our experimental results show that the proposed method is efficient and effective for image fusion compared with many other image fusion methods.\",\"PeriodicalId\":184798,\"journal\":{\"name\":\"2004 International Conference on Image Processing, 2004. ICIP '04.\",\"volume\":\"88 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 International Conference on Image Processing, 2004. ICIP '04.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2004.1419463\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Conference on Image Processing, 2004. ICIP '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2004.1419463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image fusion based on nonnegative matrix factorization
Nonnegative Matrix Factorization technique (NMF) has been shown to have various applications to image processing, because of its power of local or part-based representation of objects and/or images. In this paper, we present an image fusion method based on NMF, not by the part-based representation feature of NMF, but by its wholly representation of the images needed to be fused: the images are fused by NMF with the parameter r of the NMF to be set to 1. Our experimental results show that the proposed method is efficient and effective for image fusion compared with many other image fusion methods.