{"title":"使用超分辨率制图的土地覆盖形状表征","authors":"A. M. Muad","doi":"10.1109/ICSGRC.2017.8070568","DOIUrl":null,"url":null,"abstract":"This paper presents a representation of land cover from a popular low spatial resolution of remote sensing image, MODIS 250 m. The spatial resolution of the MODIS image is enhanced using super-resolution mapping to a resolution that is equal to resolution of Landsat ETM+, which is 30 m. Two super-resolution mapping techniques, Hopfleld neural network and pixel swapping are used to represent the land covers as patch objects. Parameters for both techniques are varies to investigate their impact towards the characterization of the object in a single MODIS image and also in a time-series MODIS images.","PeriodicalId":182418,"journal":{"name":"2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shape characterization of land covers using super-resolution mapping\",\"authors\":\"A. M. Muad\",\"doi\":\"10.1109/ICSGRC.2017.8070568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a representation of land cover from a popular low spatial resolution of remote sensing image, MODIS 250 m. The spatial resolution of the MODIS image is enhanced using super-resolution mapping to a resolution that is equal to resolution of Landsat ETM+, which is 30 m. Two super-resolution mapping techniques, Hopfleld neural network and pixel swapping are used to represent the land covers as patch objects. Parameters for both techniques are varies to investigate their impact towards the characterization of the object in a single MODIS image and also in a time-series MODIS images.\",\"PeriodicalId\":182418,\"journal\":{\"name\":\"2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC)\",\"volume\":\"128 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSGRC.2017.8070568\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSGRC.2017.8070568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Shape characterization of land covers using super-resolution mapping
This paper presents a representation of land cover from a popular low spatial resolution of remote sensing image, MODIS 250 m. The spatial resolution of the MODIS image is enhanced using super-resolution mapping to a resolution that is equal to resolution of Landsat ETM+, which is 30 m. Two super-resolution mapping techniques, Hopfleld neural network and pixel swapping are used to represent the land covers as patch objects. Parameters for both techniques are varies to investigate their impact towards the characterization of the object in a single MODIS image and also in a time-series MODIS images.
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