Divergence to Concentration and Population to Individual: A Progressive Approaching Ship Detection Paradigm for Synthetic Aperture Radar Remote Sensing Imagery

Most previous work bluntly detected individual ships from synthetic aperture radar (SAR) images, which was crude and imprecise, resulting in the loss of spatial population perception information. Inspired by the population receptive field (pRF) of biological neurology, we propose a progressive approach to ship detection paradigm for SAR remote sensing imagery in this article, that is, divergence to COncentration and POpulation to individual, named COPO. From divergence to concentration refers to predicting different ranges of ship populations via aggregating the weak direction estimation of two keypoints. This is an iterative process of gradually approaching from the edge of the image to the ship population, which is superior to directly and roughly regressing the bounding box from the image. From population to individual refers to the step-by-step localization of each ship from different populations, rather than directly arriving in one step from the image. This is a gradually emerging process of the ship target from coarse to fine and from global to local, which conforms to the pRF criterion in the human visual system. Additionally, COPO transmits ship population information to the main-branch strong detector to guide the self-attention reference point sampling of the encoder and the dynamic anchor box query of the decoder. This variant DEtection TRansformer (DETR) is known as COPO-DETR. Results on the public SSDD and HRSID datasets reveal the validity of COPO and the state-of-the-art accuracy of COPO-DETR.

• Publication year

  2026

• Venue

  IEEE Transactions on Aerospace and Electronic Systems

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1109/TAES.2025.3631066
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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