{"title":"具有非负性约束的反射光谱恢复","authors":"K. Inoue, K. Hara, K. Urahama","doi":"10.1109/ISPACS.2016.7824687","DOIUrl":null,"url":null,"abstract":"We propose two methods for recovering the reflectance spectra of given colorimetric data by using the nonnegative constraints in reflectance spectra. We formulate the problem of reflectance spectra recovery as a non-negative least squares problem and solve it with two iterative methods. Experimental results demonstrate that the two methods give similar recovery results, where Macbeth ColorChecker data are used for recovering the reflectance spectra of Neugebauer primary colors. We also transform the recovered reflectance spectra into tristimulus values to visualize them, where an ad hoc scaling operation is introduced for brightening the recovered colors.","PeriodicalId":131543,"journal":{"name":"2016 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Reflectance spectra recovery with non-negativity constraints\",\"authors\":\"K. Inoue, K. Hara, K. Urahama\",\"doi\":\"10.1109/ISPACS.2016.7824687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose two methods for recovering the reflectance spectra of given colorimetric data by using the nonnegative constraints in reflectance spectra. We formulate the problem of reflectance spectra recovery as a non-negative least squares problem and solve it with two iterative methods. Experimental results demonstrate that the two methods give similar recovery results, where Macbeth ColorChecker data are used for recovering the reflectance spectra of Neugebauer primary colors. We also transform the recovered reflectance spectra into tristimulus values to visualize them, where an ad hoc scaling operation is introduced for brightening the recovered colors.\",\"PeriodicalId\":131543,\"journal\":{\"name\":\"2016 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPACS.2016.7824687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPACS.2016.7824687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reflectance spectra recovery with non-negativity constraints
We propose two methods for recovering the reflectance spectra of given colorimetric data by using the nonnegative constraints in reflectance spectra. We formulate the problem of reflectance spectra recovery as a non-negative least squares problem and solve it with two iterative methods. Experimental results demonstrate that the two methods give similar recovery results, where Macbeth ColorChecker data are used for recovering the reflectance spectra of Neugebauer primary colors. We also transform the recovered reflectance spectra into tristimulus values to visualize them, where an ad hoc scaling operation is introduced for brightening the recovered colors.