{"title":"An Experimental Performance Evaluation of Satellite Imagery Enhancement and Segmentation Techniques for Effective Visual Display","authors":"Neetu Manocha, Rajeev Gupta","doi":"10.1109/IC3IOT53935.2022.9767946","DOIUrl":null,"url":null,"abstract":"The satellite imagery captured by high-density cameras available with satellites comprises heaps of meta-data and other related statistics about the Earth's external layer. In any case either obscure lights, different weather conditions, or other reasons, the worth of these photographs is fall down. Well known investigators suggested various algorithms for satellite imagery improvement. Regardless, after the distinct exploration, the makers have investigated that most of the current methods doesn't convey a precise outcome. With the continuation of exploration, the authors have proposed a Satellite imagery improvement and enhancement structure named SIE-EVD, to lessen the dullness or noise of satellite imagery without dropping high-review smoothness for the dominant pictorial show by means of CBIR. The authors have likewise proposed a hybrid segmentation technique named HIST-SI for satellite imagery to reduce the division error rate. In this paper, the authors examined a definite experimental execution assessment of proposed Satellite Image Enhancement and Segmentation Techniques for Effective Visual Display. After the experimentation, the authors saw that the proposed methods are showing better results for satellite imagery.","PeriodicalId":430809,"journal":{"name":"2022 International Conference on Communication, Computing and Internet of Things (IC3IoT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Communication, Computing and Internet of Things (IC3IoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3IOT53935.2022.9767946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The satellite imagery captured by high-density cameras available with satellites comprises heaps of meta-data and other related statistics about the Earth's external layer. In any case either obscure lights, different weather conditions, or other reasons, the worth of these photographs is fall down. Well known investigators suggested various algorithms for satellite imagery improvement. Regardless, after the distinct exploration, the makers have investigated that most of the current methods doesn't convey a precise outcome. With the continuation of exploration, the authors have proposed a Satellite imagery improvement and enhancement structure named SIE-EVD, to lessen the dullness or noise of satellite imagery without dropping high-review smoothness for the dominant pictorial show by means of CBIR. The authors have likewise proposed a hybrid segmentation technique named HIST-SI for satellite imagery to reduce the division error rate. In this paper, the authors examined a definite experimental execution assessment of proposed Satellite Image Enhancement and Segmentation Techniques for Effective Visual Display. After the experimentation, the authors saw that the proposed methods are showing better results for satellite imagery.