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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Ground Control Point Generation from Simulated SAR Image Derived from Digital Terrain Model and its Application to Texture Feature Extraction

Author 1: Kohei Arai

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120112

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 1, 2021.

  • Abstract and Keywords
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Abstract: Ground Control Point: GCP generation from simulated topographic map derived from Digital Terrain Model: DTM is proposed. Also, texture feature extraction is attempted from the simulated image. In this study, simulated image is derived from elevation data only, under assumptions of a simple scattering model without consideration of complex dielectric constant of the targets of interest. The performance of the acquired GCPs was evaluated by using several measures with texture features of GCP chip images. This paper describes the details about proposed method for acquisition of GCPs and simulated results on relationship between texture features and GCP matching success rate corresponding to the cross correlation between reference and distorted GCP chip images.

Keywords: Ground Control Point: GCP; Digital Terrain Model: DTM; scattering model; complex dielectric constant; texture feature; matching success rate; GCP chip

Kohei Arai, “Ground Control Point Generation from Simulated SAR Image Derived from Digital Terrain Model and its Application to Texture Feature Extraction” International Journal of Advanced Computer Science and Applications(IJACSA), 12(1), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120112

@article{Arai2021,
title = {Ground Control Point Generation from Simulated SAR Image Derived from Digital Terrain Model and its Application to Texture Feature Extraction},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120112},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120112},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {1},
author = {Kohei Arai}
}


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