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Cover Article | Open Access

Density-based ship detection in SAR images: Extension to a self-similarity perspective

Xueqian WANGa, Gang LIa( ), Zhizhuo JIANGb, Yu LIUa, You HEa
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China

Peer review under responsibility of Editorial Committee of CJA.

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Abstract

Nonlocal self-similarity is an important property of Synthetic Aperture Radar (SAR) images to characterize the repetitiveness of features embodied by SAR images within nonlocal areas and has been used for enhancement of SAR images. Existing SAR ship detectors often independently handle small sub-images cropped from a large marine SAR image and do not exploit the nonlocal self-similarity therein. In this paper, we propose a new ship detector from the perspective of nonlocal self-similarity in SAR images to improve the ship detection performance, basically including three stages: prescreening, intra-cue calculation, and inter-cue calculation. In the pre-screening stage, we design a new Histogram-based Density (HD) feature to rapidly select candidate sub-images potentially containing ship targets from a large SAR image. In the intra-cue calculation stage, target cues within a single candidate sub-image are extracted. In the inter-cue calculation stage, thanks to the nonlocal self-similarity among different candidate sub-images in terms of density features, we innovatively extract a weighted superpixel-HD map to obtain accumulated intra-cues across all the candidate sub-images. Finally, for each candidate sub-image, we fuse its inter-cue and intra-cue to obtain final detection results. Experimental results based on real SAR images show that our newly proposed method provides a better target-to-clutter contrast and ship detection performance than those of other state-of-the-art detection approaches.

Keywords

Ship detectionSynthetic aperture radar (SAR)DensitySelf-similarityHistogram

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Chinese Journal of Aeronautics
Volume 37 Issue 3,
March 2024
Pages 168-180
DOI: 10.1016/j.cja.2023.11.017
Cite this article:
WANG X, LI G, JIANG Z, et al. Density-based ship detection in SAR images: Extension to a self-similarity perspective. Chinese Journal of Aeronautics, 2024, 37(3): 168-180. https://doi.org/10.1016/j.cja.2023.11.017

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Received: 20 March 2023
Revised: 09 April 2023
Accepted: 01 June 2023
Published: 24 November 2023
© 2023 Chinese Society of Aeronautics and Astronautics.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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