{"title":"基于稀疏度的高光谱图像泛锐化新算法","authors":"C. Kwan, Bence Budavari, Minh Dao, Jin Zhou","doi":"10.1109/UEMCON.2017.8248993","DOIUrl":null,"url":null,"abstract":"In this paper, we present new sparsity based algorithms in generating a high resolution hyperspectral image by fusing a high resolution color image with a low resolution hyperspectral image. Mathematical formulation of the sparsity based approaches is presented. Comparison with other pansharpening algorithms using actual data has been carried out using two hyperspectral image data sets. Initial results are encouraging. Most importantly, the new sparsity formulation points to a new direction in generating high resolution hyperspectral images where the raw images may be noisy.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":"2008 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"New sparsity based pansharpening algorithms for hyperspectral images\",\"authors\":\"C. Kwan, Bence Budavari, Minh Dao, Jin Zhou\",\"doi\":\"10.1109/UEMCON.2017.8248993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present new sparsity based algorithms in generating a high resolution hyperspectral image by fusing a high resolution color image with a low resolution hyperspectral image. Mathematical formulation of the sparsity based approaches is presented. Comparison with other pansharpening algorithms using actual data has been carried out using two hyperspectral image data sets. Initial results are encouraging. Most importantly, the new sparsity formulation points to a new direction in generating high resolution hyperspectral images where the raw images may be noisy.\",\"PeriodicalId\":403890,\"journal\":{\"name\":\"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)\",\"volume\":\"2008 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UEMCON.2017.8248993\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UEMCON.2017.8248993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New sparsity based pansharpening algorithms for hyperspectral images
In this paper, we present new sparsity based algorithms in generating a high resolution hyperspectral image by fusing a high resolution color image with a low resolution hyperspectral image. Mathematical formulation of the sparsity based approaches is presented. Comparison with other pansharpening algorithms using actual data has been carried out using two hyperspectral image data sets. Initial results are encouraging. Most importantly, the new sparsity formulation points to a new direction in generating high resolution hyperspectral images where the raw images may be noisy.