Probabilistic analysis and evaluation of classical line error band models of ε-band, G-band, and standard deviation band

Lejingyi Zhou; Yanmin Jin; Xiaohua Tong

doi:10.1117/12.2665822

31 January 2023 Probabilistic analysis and evaluation of classical line error band models of ε-band, G-band, and standard deviation band

Lejingyi Zhou, Yanmin Jin, Xiaohua Tong

Author Affiliations +

Proceedings Volume 12505, Earth and Space: From Infrared to Terahertz (ESIT 2022); 1250528 (2023) https://doi.org/10.1117/12.2665822
Event: Earth and Space: From Infrared to Terahertz (ESIT 2022), 2022, Nantong, China

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.

Citation Download Citation

Lejingyi Zhou, Yanmin Jin, and Xiaohua Tong "Probabilistic analysis and evaluation of classical line error band models of ε-band, G-band, and standard deviation band", Proc. SPIE 12505, Earth and Space: From Infrared to Terahertz (ESIT 2022), 1250528 (31 January 2023); https://doi.org/10.1117/12.2665822

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