TY - GEN
T1 - Generalized likelihood ratio tests for linear structure detection in SAR images
AU - Gasnier, Nicolas
AU - Denis, Loïc
AU - Tupin, Florence
N1 - Publisher Copyright:
© VDE VERLAG GMBH . Berlin . Offenbach
PY - 2021/1/1
Y1 - 2021/1/1
N2 - The detection of linear structures in Synthetic Aperture Radar images is often used as a first step for further processing such as the extraction of road and river networks. In this paper, we propose a new method based on the Generalized Likelihood Ratio Test (GLRT) framework to evaluate at each pixel the likelihood of the presence of a linear structure. Results are presented on Sentinel-1 images and compared with a state-of-the-art method, also derived from the GLRT framework but with a simpler model of the lines. In our experiments, our method produces far fewer false positives than the reference method.
AB - The detection of linear structures in Synthetic Aperture Radar images is often used as a first step for further processing such as the extraction of road and river networks. In this paper, we propose a new method based on the Generalized Likelihood Ratio Test (GLRT) framework to evaluate at each pixel the likelihood of the presence of a linear structure. Results are presented on Sentinel-1 images and compared with a state-of-the-art method, also derived from the GLRT framework but with a simpler model of the lines. In our experiments, our method produces far fewer false positives than the reference method.
UR - https://www.scopus.com/pages/publications/85101950242
M3 - Conference contribution
AN - SCOPUS:85101950242
T3 - Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
SP - 140
EP - 145
BT - EUSAR 2021 - 13th European Conference on Synthetic Aperture Radar, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th European Conference on Synthetic Aperture Radar, EUSAR 2021
Y2 - 29 March 2021 through 1 April 2021
ER -