{"title":"基于超分辨率技术的多光谱图像贝叶斯重建参数估计","authors":"R. Molina, M. Vega, J. Mateos, A. Katsaggelos","doi":"10.1109/ICIP.2006.312720","DOIUrl":null,"url":null,"abstract":"In this paper we present a new super resolution Bayesian method for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of the multispectral images, b) uses the sensor characteristics to model the observation process of both panchromatic and multispectral images, and c) performs the estimation of all the unknown parameters in the model. Using real data, the pansharpened multispectral images are compared with the images obtained by other pansharpening methods and their quality is assessed both qualitatively and quantitatively.","PeriodicalId":299355,"journal":{"name":"2006 International Conference on Image Processing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Parameter Estimation in Bayesian Reconstruction of Multispectral Images using Super Resolution Techniques\",\"authors\":\"R. Molina, M. Vega, J. Mateos, A. Katsaggelos\",\"doi\":\"10.1109/ICIP.2006.312720\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a new super resolution Bayesian method for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of the multispectral images, b) uses the sensor characteristics to model the observation process of both panchromatic and multispectral images, and c) performs the estimation of all the unknown parameters in the model. Using real data, the pansharpened multispectral images are compared with the images obtained by other pansharpening methods and their quality is assessed both qualitatively and quantitatively.\",\"PeriodicalId\":299355,\"journal\":{\"name\":\"2006 International Conference on Image Processing\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2006.312720\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2006.312720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parameter Estimation in Bayesian Reconstruction of Multispectral Images using Super Resolution Techniques
In this paper we present a new super resolution Bayesian method for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of the multispectral images, b) uses the sensor characteristics to model the observation process of both panchromatic and multispectral images, and c) performs the estimation of all the unknown parameters in the model. Using real data, the pansharpened multispectral images are compared with the images obtained by other pansharpening methods and their quality is assessed both qualitatively and quantitatively.
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