Noise Reduced SAR Ship Database

Hanbay K., Üzen H., Özdemir T. B., Erçelik Ç.

2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Turkey, 21 - 22 September 2024, vol.8, pp.1-6, (Full Text)

  • Publication Type: Conference Paper / Full Text
  • Volume: 8
  • Doi Number: 10.1109/idap64064.2024.10710785
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.1-6
  • Inonu University Affiliated: Yes

Abstract

Synthetic aperture radar (SAR) images are used extensively in agricultural applications, coastal boundary detection and object recognition. This imaging technology provides desired results in many challenging applications due to its ability to provide images with appropriate resolution in harsh weather and climate conditions. In this study, an image database was created to detect ships from SAR images. The images were preprocessed in accordance with the literature and made suitable for ship detection methods. The noise in the images was reduced with a deep learning-based architecture. Using this database, image processing and machine learning methods were used to develop ship detection methods.