{"title":"分析了图像噪声和采样间隔对分辨率增强的影响","authors":"Nureddin A. F. Aldali, Miao Jun-gang","doi":"10.1109/COMPCOMM.2016.7924760","DOIUrl":null,"url":null,"abstract":"These days satellite images are being used in different fields, so it is essential for those images to have high resolution. Satellite images are affected by various factors in space such as: absorption, scattering, etc. Resolution of those images is very low. To have better perception of these images it is necessary to have the image with clear and well defined edges, which provides better visible line of separation. Resolution enhancement of these images has always been a major issue to extract more information from them. GEO Satellite imagery is an important tool and can be used to estimate rainfall during the thunderstorms and hurricanes for flash flood warnings in real time. However, for the GEO satellite is located higher than normal LEO satellite, the spatial resolution images are lower. Therefore, in order to obtain an image with enough resolution, some methods are to be implemented in GEO satellite observation such as: resolution enhancement which is a technique that achieves higher resolution for satellite image with lower resolution. There are many approaches that can be used to enhance the resolution of a satellite image. This paper focuses on the comparison between two techniques that are used to increase resolution of the images. Noise and sampling interval techniques, the two algorithms are shown via simulation. The simulation is introduced, and the results are discussed.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of the effect of image noise and sampling interval on the resolution enhancement\",\"authors\":\"Nureddin A. F. Aldali, Miao Jun-gang\",\"doi\":\"10.1109/COMPCOMM.2016.7924760\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"These days satellite images are being used in different fields, so it is essential for those images to have high resolution. Satellite images are affected by various factors in space such as: absorption, scattering, etc. Resolution of those images is very low. To have better perception of these images it is necessary to have the image with clear and well defined edges, which provides better visible line of separation. Resolution enhancement of these images has always been a major issue to extract more information from them. GEO Satellite imagery is an important tool and can be used to estimate rainfall during the thunderstorms and hurricanes for flash flood warnings in real time. However, for the GEO satellite is located higher than normal LEO satellite, the spatial resolution images are lower. Therefore, in order to obtain an image with enough resolution, some methods are to be implemented in GEO satellite observation such as: resolution enhancement which is a technique that achieves higher resolution for satellite image with lower resolution. There are many approaches that can be used to enhance the resolution of a satellite image. This paper focuses on the comparison between two techniques that are used to increase resolution of the images. Noise and sampling interval techniques, the two algorithms are shown via simulation. The simulation is introduced, and the results are discussed.\",\"PeriodicalId\":210833,\"journal\":{\"name\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPCOMM.2016.7924760\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPCOMM.2016.7924760","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of the effect of image noise and sampling interval on the resolution enhancement
These days satellite images are being used in different fields, so it is essential for those images to have high resolution. Satellite images are affected by various factors in space such as: absorption, scattering, etc. Resolution of those images is very low. To have better perception of these images it is necessary to have the image with clear and well defined edges, which provides better visible line of separation. Resolution enhancement of these images has always been a major issue to extract more information from them. GEO Satellite imagery is an important tool and can be used to estimate rainfall during the thunderstorms and hurricanes for flash flood warnings in real time. However, for the GEO satellite is located higher than normal LEO satellite, the spatial resolution images are lower. Therefore, in order to obtain an image with enough resolution, some methods are to be implemented in GEO satellite observation such as: resolution enhancement which is a technique that achieves higher resolution for satellite image with lower resolution. There are many approaches that can be used to enhance the resolution of a satellite image. This paper focuses on the comparison between two techniques that are used to increase resolution of the images. Noise and sampling interval techniques, the two algorithms are shown via simulation. The simulation is introduced, and the results are discussed.