{"title":"Hyperion高光谱数据的空间分辨率增强","authors":"K. Nikolakopoulos","doi":"10.1109/WHISPERS.2009.5288996","DOIUrl":null,"url":null,"abstract":"In this study eight fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (Modihs), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. Both sensors are part of the Earth-Observing 1 satellite. The panchromatic data have a spatial resolution of 10m while the hyperspectral data have a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data.","PeriodicalId":242447,"journal":{"name":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Spatial resolution enhancement of Hyperion hyperspectral data\",\"authors\":\"K. Nikolakopoulos\",\"doi\":\"10.1109/WHISPERS.2009.5288996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study eight fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (Modihs), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. Both sensors are part of the Earth-Observing 1 satellite. The panchromatic data have a spatial resolution of 10m while the hyperspectral data have a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data.\",\"PeriodicalId\":242447,\"journal\":{\"name\":\"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WHISPERS.2009.5288996\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WHISPERS.2009.5288996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
本研究采用Ehlers、Gram-Schmidt、High Pass Filter、Local Mean Matching (LMM)、Local Mean and Variance Matching (LMVM)、Modified IHS (Modihs)、Pansharp和PCA等8种融合技术对Hyperion高光谱数据与ALI全色数据进行融合。这两个传感器都是地球观测1号卫星的一部分。全色数据的空间分辨率为10m,高光谱数据的空间分辨率为30m。所有的融合技术都是为经典多光谱数据设计的。因此,研究常用的融合算法与高光谱数据的评估是非常有趣的。
Spatial resolution enhancement of Hyperion hyperspectral data
In this study eight fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (Modihs), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. Both sensors are part of the Earth-Observing 1 satellite. The panchromatic data have a spatial resolution of 10m while the hyperspectral data have a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data.