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LocSAR: a location-based SAR ship generation model for complex backgrounds

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Abstract

Due to its good performance, synthetic aperture radar (SAR) is gradually regarded as a favorable tool to solve the target detection task, especially in marine target detection. Maritime target detection models always need a lot of SAR images for learning, but in fact the use of SAR images has limitations so the acquisition of SAR images is a problem. In addition to this, the labeling of the target is also a time consuming and labor intensive process. In order to solve these problems, we propose a location-based SAR generation model, referred to as the LocSAR, which takes the target position and category information as inputs and outputs location-specific high-quality complex SAR images. The model consists of four parts: a cascade Encoder-Decoder, a scene fusion module, a feature fusion module and a discriminator. We use the feature fusion module to fuse the features of neighboring resolution images and introduce the scene fusion module for semantic information learning. The Encoder-Decoder implements feature extraction and reconstruction, while the discriminator is used for adversarial training. We also use gradient variance loss to improve the quality of the generated images. We updated the existing data set HRSID with the addition of land and sea labels and conducted experiments on this. Extensive experiments show that our model is excellent to classic image generation models. We have also designed a simple interface to assist in image generation and labeling, which can be directly applied to the other model.

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Data availability

No datasets were generated or analysed during the current study.

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Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 62201114 and Grant 62301108; in part by the Scientific Research Fund of Liaoning Provincial Education Department under Grant JYTMS20230171 and Grant JYTMS20230176; in part by the Fundamental Research Funds for the Central Universities under Grant 3132024237.

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Contributions

M. J. and M. L. contributed to this work by designing the algorithms, analyzing the data and writing the paper. T. M. and N. N. contributed to set up the experimental environment and performed the experiments. D. F. and S. J. contributed through research supervisory and reviewer role by amending the paper.

Corresponding authors

Correspondence to Mulin Li or Sinian Jin.

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Ju, M., Li, M., Mao, T. et al. LocSAR: a location-based SAR ship generation model for complex backgrounds. SIViP 19, 78 (2025). https://doi.org/10.1007/s11760-024-03605-3

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  • DOI: https://doi.org/10.1007/s11760-024-03605-3

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