Side Scan Sonar Image Super Resolution via Region-Selective Sparse Coding

Jaihyun PARK  Bonhwa KU  Youngsaeng JIN  Hanseok KO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.1   pp.210-213
Publication Date: 2019/01/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8170
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
Keyword: 
side scan sonar,  super resolution,  sparse coding,  object detection,  

Full Text: PDF(1MB)
>>Buy this Article


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.