Generating and correcting rational polynomial coefficients using image correction model

Namhoon Kim, Hyo Seon Jang, Mohammad Gholami Farkoushi, Yoon Jo Choi, Hong Gyoo Sohn

Research output: Contribution to conferencePaper

Abstract

We propose a method to regenerate and correct Rational Polynomial Coefficients (RPCs) using KOMPSAT-3A imagery. Physical sensor model of KOMPSAT-3A and virtual grid over the target area were used to estimate the new RPCs. Three different image correction models (image coordinate translation model, shift and drift model, and affine transformation model) were used to remove image space error. We tested our method in Seoul and Goheung area. When using un-corrected new RPCs, the results showed a 20-30 pixel error. After applying image correction models, the error reduced to 1.8 to 5.5 pixels. The expected error map was generated from the error propagation analysis using Gauss-Markov Model.

Original languageEnglish
Publication statusPublished - 2020 Jan 1
Event40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 - Daejeon, Korea, Republic of
Duration: 2019 Oct 142019 Oct 18

Conference

Conference40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019
CountryKorea, Republic of
CityDaejeon
Period19/10/1419/10/18

All Science Journal Classification (ASJC) codes

  • Information Systems

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    Kim, N., Jang, H. S., Farkoushi, M. G., Choi, Y. J., & Sohn, H. G. (2020). Generating and correcting rational polynomial coefficients using image correction model. Paper presented at 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019, Daejeon, Korea, Republic of.