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
Le sonar à balayage latéral utilisant les basses fréquences peut rechercher rapidement une large plage, mais les images acquises sont de mauvaise qualité. La méthode de super résolution d'image (SR) peut atténuer ce problème. La méthode SR utilise généralement un codage clairsemé, mais l’estimation précise de coefficients clairsemés entraîne des coûts de calcul importants. Pour réduire le temps de traitement, nous proposons un système SR basé sur un codage clairsemé sélectif par région qui met l'accent sur les régions d'objets. En particulier, la région qui contient des objets intéressants est détectée pour des images sous-marines basées sur un sonar à balayage latéral de sorte que le processus SR basé sur un codage clairsemé ultérieur puisse être appliqué de manière sélective. L'efficacité de la méthode proposée est vérifiée par le temps de traitement réduit requis pour la reconstruction de l'image tout en préservant le même niveau de qualité visuelle que les méthodes conventionnelles.
Jaihyun PARK
Korea University
Bonhwa KU
Korea University
Youngsaeng JIN
Korea University
Hanseok KO
Korea University
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Jaihyun PARK, Bonhwa KU, Youngsaeng JIN, Hanseok KO, "Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 1, pp. 210-213, January 2019, doi: 10.1587/transinf.2018EDL8170.
Abstract: Side scan sonar using low frequency can quickly search a wide range, but the images acquired are of low quality. The image super resolution (SR) method can mitigate this problem. The SR method typically uses sparse coding, but accurately estimating sparse coefficients incurs substantial computational costs. To reduce processing time, we propose a region-selective sparse coding based SR system that emphasizes object regions. In particular, the region that contains interesting objects is detected for side scan sonar based underwater images so that the subsequent sparse coding based SR process can be selectively applied. Effectiveness of the proposed method is verified by the reduced processing time required for image reconstruction yet preserving the same level of visual quality as conventional methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDL8170/_p
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@ARTICLE{e102-d_1_210,
author={Jaihyun PARK, Bonhwa KU, Youngsaeng JIN, Hanseok KO, },
journal={IEICE TRANSACTIONS on Information},
title={Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding},
year={2019},
volume={E102-D},
number={1},
pages={210-213},
abstract={Side scan sonar using low frequency can quickly search a wide range, but the images acquired are of low quality. The image super resolution (SR) method can mitigate this problem. The SR method typically uses sparse coding, but accurately estimating sparse coefficients incurs substantial computational costs. To reduce processing time, we propose a region-selective sparse coding based SR system that emphasizes object regions. In particular, the region that contains interesting objects is detected for side scan sonar based underwater images so that the subsequent sparse coding based SR process can be selectively applied. Effectiveness of the proposed method is verified by the reduced processing time required for image reconstruction yet preserving the same level of visual quality as conventional methods.},
keywords={},
doi={10.1587/transinf.2018EDL8170},
ISSN={1745-1361},
month={January},}
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TY - JOUR
TI - Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding
T2 - IEICE TRANSACTIONS on Information
SP - 210
EP - 213
AU - Jaihyun PARK
AU - Bonhwa KU
AU - Youngsaeng JIN
AU - Hanseok KO
PY - 2019
DO - 10.1587/transinf.2018EDL8170
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2019
AB - Side scan sonar using low frequency can quickly search a wide range, but the images acquired are of low quality. The image super resolution (SR) method can mitigate this problem. The SR method typically uses sparse coding, but accurately estimating sparse coefficients incurs substantial computational costs. To reduce processing time, we propose a region-selective sparse coding based SR system that emphasizes object regions. In particular, the region that contains interesting objects is detected for side scan sonar based underwater images so that the subsequent sparse coding based SR process can be selectively applied. Effectiveness of the proposed method is verified by the reduced processing time required for image reconstruction yet preserving the same level of visual quality as conventional methods.
ER -