IEICE TRANSACTIONS on Information
Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.1 pp.210-213
- Publication Date
- 2019/01/01
- Publicized
- 2018/10/22
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2018EDL8170
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Jaihyun PARK
Korea University
Bonhwa KU
Korea University
Youngsaeng JIN
Korea University
Hanseok KO
Korea University
Keyword
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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},}
Copy
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 -
English
