{"title":"Landsat-8传感器和Sentinel-2传感器数据融合与多尺度详细信息","authors":"Peng Wang;Jun Du;Xiongfei Wen;Caiping Hu;Lin Ge;Mingxuan Huang","doi":"10.1109/LSENS.2024.3499361","DOIUrl":null,"url":null,"abstract":"<?Firstputimage>\nWith the increasing demand for high temporal and spatial resolution multispectral data sequences, many studies have been carried out on fusion on Landsat-8 and Sentinel-2 sensor data. However, current fusion methods suffer from the loss of detailed spatial and spectral information. To address this problem, a Landsat-8 and Sentinel-2 data fusion with multiscale detailed information (MSDI) method is proposed. MSDI combines well the initial spatial prediction obtained from the Landsat-8 data at the target date and the detailed part extracted from the Sentinel-2 data at the reference date. Thin plate spline interpolation is implemented on the Landsat-8 data for upsampling. Smoothing-sharpening filter (SSIF) is employed to separate the high- and low-frequency components of data from the two sensors. The multiscale SSIF is then utilized to migrate the details from the Sentinel-2 data to the upsampled Landsat-8 data. Experiments at two sites confirm that the proposed MSDI method could efficiently generate Sentinel-2-like data with high spatial and spectral resolution.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 12","pages":"1-4"},"PeriodicalIF":2.2000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Landsat-8 Sensor and Sentinel-2 Sensor Data Fusion With Multiscale Detailed Information\",\"authors\":\"Peng Wang;Jun Du;Xiongfei Wen;Caiping Hu;Lin Ge;Mingxuan Huang\",\"doi\":\"10.1109/LSENS.2024.3499361\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<?Firstputimage>\\nWith the increasing demand for high temporal and spatial resolution multispectral data sequences, many studies have been carried out on fusion on Landsat-8 and Sentinel-2 sensor data. However, current fusion methods suffer from the loss of detailed spatial and spectral information. To address this problem, a Landsat-8 and Sentinel-2 data fusion with multiscale detailed information (MSDI) method is proposed. MSDI combines well the initial spatial prediction obtained from the Landsat-8 data at the target date and the detailed part extracted from the Sentinel-2 data at the reference date. Thin plate spline interpolation is implemented on the Landsat-8 data for upsampling. Smoothing-sharpening filter (SSIF) is employed to separate the high- and low-frequency components of data from the two sensors. The multiscale SSIF is then utilized to migrate the details from the Sentinel-2 data to the upsampled Landsat-8 data. Experiments at two sites confirm that the proposed MSDI method could efficiently generate Sentinel-2-like data with high spatial and spectral resolution.\",\"PeriodicalId\":13014,\"journal\":{\"name\":\"IEEE Sensors Letters\",\"volume\":\"8 12\",\"pages\":\"1-4\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10753512/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10753512/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Landsat-8 Sensor and Sentinel-2 Sensor Data Fusion With Multiscale Detailed Information
With the increasing demand for high temporal and spatial resolution multispectral data sequences, many studies have been carried out on fusion on Landsat-8 and Sentinel-2 sensor data. However, current fusion methods suffer from the loss of detailed spatial and spectral information. To address this problem, a Landsat-8 and Sentinel-2 data fusion with multiscale detailed information (MSDI) method is proposed. MSDI combines well the initial spatial prediction obtained from the Landsat-8 data at the target date and the detailed part extracted from the Sentinel-2 data at the reference date. Thin plate spline interpolation is implemented on the Landsat-8 data for upsampling. Smoothing-sharpening filter (SSIF) is employed to separate the high- and low-frequency components of data from the two sensors. The multiscale SSIF is then utilized to migrate the details from the Sentinel-2 data to the upsampled Landsat-8 data. Experiments at two sites confirm that the proposed MSDI method could efficiently generate Sentinel-2-like data with high spatial and spectral resolution.