{"title":"Probabilistic analysis and evaluation of classical line error band models of ε-band, G-band, and standard deviation band","authors":"Lejingyi Zhou, Yanmin Jin, X. Tong","doi":"10.1117/12.2665822","DOIUrl":null,"url":null,"abstract":"The line error band models have been extensively used for evaluating the position errors of the line features in surveying, remote sensing, etc.. Although there have been several classical line error band models, the shapes and the probabilities of those models have not been unified. In this paper, the probabilities of line segment falling in its several representative line error bands, namely ε-band, G-band and standard deviation band, are estimated though simulated experiments. A probability-related evaluation index is proposed to evaluate the error models with the aim to provide suggestions for selection of different error models in various scenarios.","PeriodicalId":258680,"journal":{"name":"Earth and Space From Infrared to Terahertz (ESIT 2022)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth and Space From Infrared to Terahertz (ESIT 2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2665822","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 line error band models have been extensively used for evaluating the position errors of the line features in surveying, remote sensing, etc.. Although there have been several classical line error band models, the shapes and the probabilities of those models have not been unified. In this paper, the probabilities of line segment falling in its several representative line error bands, namely ε-band, G-band and standard deviation band, are estimated though simulated experiments. A probability-related evaluation index is proposed to evaluate the error models with the aim to provide suggestions for selection of different error models in various scenarios.