{"title":"一种光谱成像系统及光谱函数恢复算法","authors":"S. Tominaga, R. Okajima","doi":"10.1109/IAI.2000.839616","DOIUrl":null,"url":null,"abstract":"Knowledge of such spectral functions as the surface-spectral reflectances of objects and the illuminant spectral power distribution is needed for realizing color constancy, accurate color reproduction, and rendering realistic images. This paper describes a spectral-imaging system using a liquid-crystal tunable filter and algorithms for recovering the spectral functions of illuminant and surface reflectance from the image data. First, we introduce a filtering mechanism and the camera system. Next, the camera outputs and the spectral functions are represented by finite-dimensional linear models. The algorithms for estimating the spectral functions are then presented using the image data. Finally the usefulness of the proposed imaging system and algorithms is shown in an experiment.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A spectral-imaging system and algorithms for recovering spectral functions\",\"authors\":\"S. Tominaga, R. Okajima\",\"doi\":\"10.1109/IAI.2000.839616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Knowledge of such spectral functions as the surface-spectral reflectances of objects and the illuminant spectral power distribution is needed for realizing color constancy, accurate color reproduction, and rendering realistic images. This paper describes a spectral-imaging system using a liquid-crystal tunable filter and algorithms for recovering the spectral functions of illuminant and surface reflectance from the image data. First, we introduce a filtering mechanism and the camera system. Next, the camera outputs and the spectral functions are represented by finite-dimensional linear models. The algorithms for estimating the spectral functions are then presented using the image data. Finally the usefulness of the proposed imaging system and algorithms is shown in an experiment.\",\"PeriodicalId\":224112,\"journal\":{\"name\":\"4th IEEE Southwest Symposium on Image Analysis and Interpretation\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"4th IEEE Southwest Symposium on Image Analysis and Interpretation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAI.2000.839616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI.2000.839616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A spectral-imaging system and algorithms for recovering spectral functions
Knowledge of such spectral functions as the surface-spectral reflectances of objects and the illuminant spectral power distribution is needed for realizing color constancy, accurate color reproduction, and rendering realistic images. This paper describes a spectral-imaging system using a liquid-crystal tunable filter and algorithms for recovering the spectral functions of illuminant and surface reflectance from the image data. First, we introduce a filtering mechanism and the camera system. Next, the camera outputs and the spectral functions are represented by finite-dimensional linear models. The algorithms for estimating the spectral functions are then presented using the image data. Finally the usefulness of the proposed imaging system and algorithms is shown in an experiment.