Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding
- Authors
- Park, Jaihyun; Ku, Bonhwa; Jin, Youngsaeng; Ko, Hanseok
- Issue Date
- 1월-2019
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- side scan sonar; super resolution; sparse coding; object detection
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E102D, no.1, pp.210 - 213
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E102D
- Number
- 1
- Start Page
- 210
- End Page
- 213
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/68462
- DOI
- 10.1587/transinf.2018EDL8170
- ISSN
- 1745-1361
- 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.
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Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
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