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
A imagem ultrassônica é útil em observações do fundo do mar ou de lagos. Podemos estimar aproximadamente a profundidade do mar ouvindo o eco gerado pela fronteira entre água e rochas ou areia. No entanto, a qualidade da estimativa geralmente não é suficiente para desenhar a paisagem do fundo do mar, uma vez que o sinal de eco inclui distorções graves causadas por autointerferência. Este artigo propõe um novo método para visualizar a forma de limites distantes, como o limite água do mar-rocha/areia, baseado no modelo de campo aleatório de Markov de valor complexo (CMRF). Nosso método realiza compensação adaptativa de distorção sem alterar as características globais nos dados de medição e obtém uma paisagem de maior qualidade com menos custo computacional do que os métodos convencionais.
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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},}
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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 -