A Ship Wake Detection Method in SAR Images Based on Joint Sparse Representation

  • Huaping Xu*
  • , Shuangying Xiao
  • , Yanan Guan
  • , Wei Li
  • *Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

The strong sea clutter and noise in synthetic aperture radar (SAR) images will cover weak ship wakes, making it difficult for conventional ship wake detection methods to accurately detect ship wakes. A ship wake detection method based on joint sparse representation is proposed in this paper to improve the detection effect of ship wakes in complex backgrounds. Firstly, the sparse representation model of SAR images based on the Radon transform is constructed. Secondly, using dual-domain images in the spatial and gradient domains, the optimization function for ship wake detection based on joint sparse representation is constructed and solved iteratively. Then, the weighted clustering criterion based on sparse coefficient and Radon coordinates is used to perform sparse coefficient clustering, and the centerline detection of the ship wake is realized by the inverse Radon transformation of the cluster center. Finally, the experimental results of TerraSAR-X images are used to verify the effectiveness of the proposed method.

Original languageEnglish
Pages9879-9882
Number of pages4
DOIs
StatePublished - 2024
Event2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 - Athens, Greece
Duration: 7 Jul 202412 Jul 2024

Conference

Conference2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024
Country/TerritoryGreece
CityAthens
Period7/07/2412/07/24

Keywords

  • Radon transform
  • SAR images
  • ship wake detection
  • sparse representation

Fingerprint

Dive into the research topics of 'A Ship Wake Detection Method in SAR Images Based on Joint Sparse Representation'. Together they form a unique fingerprint.

Cite this