The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L’imagerie ultrasonique est utile pour l’observation des fonds marins ou des fonds lacustres. Nous pouvons estimer approximativement la profondeur de la mer en entendant l'écho généré par la limite de l'eau et des rochers ou du sable. Cependant, la qualité de l'estimation n'est généralement pas suffisante pour dessiner le paysage des fonds marins, car le signal d'écho comprend de graves distorsions causées par l'auto-interférence. Cet article propose une nouvelle méthode pour visualiser la forme de limites distantes, telles que la limite eau de mer-roche/sable, basée sur le modèle de champ aléatoire de Markov à valeurs complexes (CMRF). Notre méthode réalise une compensation adaptative de la distorsion sans modifier les caractéristiques globales des données de mesure et obtient un paysage de meilleure qualité avec un coût de calcul inférieur à celui des méthodes conventionnelles.
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Tomohiro NISHINO, Ryo YAMAKI, Akira HIROSE, "Ultrasonic Imaging for Boundary Shape Generation by Phase Unwrapping with Singular-Point Elimination Based on Complex-Valued Markov Random Field Model" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 1, pp. 219-226, January 2010, doi: 10.1587/transfun.E93.A.219.
Abstract: Ultrasonic imaging is useful in seabed or lakebed observations. We can roughly estimate the sea depth by hearing the echo generated by the boundary of water and rocks or sand. However, the estimation quality is usually not sufficient to draw seabed landscape since the echo signal includes serious distortion caused by autointerference. This paper proposes a novel method to visualize the shape of distant boundaries, such as the seawater-rock/sand boundary, based on the complex-valued Markov random field (CMRF) model. Our method realizes adaptive compensation of distortion without changing the global features in the measurement data, and obtains higher-quality landscape with less computational cost than conventional methods.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.219/_p
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@ARTICLE{e93-a_1_219,
author={Tomohiro NISHINO, Ryo YAMAKI, Akira HIROSE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Ultrasonic Imaging for Boundary Shape Generation by Phase Unwrapping with Singular-Point Elimination Based on Complex-Valued Markov Random Field Model},
year={2010},
volume={E93-A},
number={1},
pages={219-226},
abstract={Ultrasonic imaging is useful in seabed or lakebed observations. We can roughly estimate the sea depth by hearing the echo generated by the boundary of water and rocks or sand. However, the estimation quality is usually not sufficient to draw seabed landscape since the echo signal includes serious distortion caused by autointerference. This paper proposes a novel method to visualize the shape of distant boundaries, such as the seawater-rock/sand boundary, based on the complex-valued Markov random field (CMRF) model. Our method realizes adaptive compensation of distortion without changing the global features in the measurement data, and obtains higher-quality landscape with less computational cost than conventional methods.},
keywords={},
doi={10.1587/transfun.E93.A.219},
ISSN={1745-1337},
month={January},}
Copier
TY - JOUR
TI - Ultrasonic Imaging for Boundary Shape Generation by Phase Unwrapping with Singular-Point Elimination Based on Complex-Valued Markov Random Field Model
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 219
EP - 226
AU - Tomohiro NISHINO
AU - Ryo YAMAKI
AU - Akira HIROSE
PY - 2010
DO - 10.1587/transfun.E93.A.219
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2010
AB - Ultrasonic imaging is useful in seabed or lakebed observations. We can roughly estimate the sea depth by hearing the echo generated by the boundary of water and rocks or sand. However, the estimation quality is usually not sufficient to draw seabed landscape since the echo signal includes serious distortion caused by autointerference. This paper proposes a novel method to visualize the shape of distant boundaries, such as the seawater-rock/sand boundary, based on the complex-valued Markov random field (CMRF) model. Our method realizes adaptive compensation of distortion without changing the global features in the measurement data, and obtains higher-quality landscape with less computational cost than conventional methods.
ER -