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Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding
Jaihyun PARK Bonhwa KU Youngsaeng JIN Hanseok KO
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2019/01/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
side scan sonar, super resolution, sparse coding, object detection,
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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.