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Sidescan sonar image super resolution based on sparse representation

  • Liyong Ma*
  • , Xili He
  • , Zhishen Huang
  • *Corresponding author for this work
  • School of Information Science and Engineering, Harbin Institute of Technology Weihai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the rapid development of autonomous underwater vehicles, image produced from sidescan sonar mounted on these vehicles has attracted more and more attention. Many general super resolution approaches can not get satisfied results after applying to sidescan sonar image for its low levels of contrast. Compressive sensing theory suggested that high resolution image can be recovered from low resolution image with sparse representation. After training two dictionaries for high resolution and low resolution image patches, the sparse representation of given low resolution image can be applied to the dictionary of high resolution patch to get super resolution result image. Sparse representation based image super resolution approach applied to sidescan sonar image is discussed.

Original languageEnglish
Title of host publicationMeasuring Technology and Mechatronics Automation
Pages1049-1052
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 - Shanghai, China
Duration: 6 Jan 20117 Jan 2011

Publication series

NameApplied Mechanics and Materials
Volume48-49
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Country/TerritoryChina
CityShanghai
Period6/01/117/01/11

Keywords

  • Compressive sensing
  • Dictionary learning
  • Image super resolution
  • Sidescan sonar image
  • Sparse representation

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