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MSF-DETR: A small target detection algorithm for sonar images based on spatial-frequency domain collaborative feature

Heng Zhao¹, Shuping Han¹, Jiaying Geng¹

¹Naval Submarine Academy, Qingdao, China.

|November 14, 2025

Summary

This study introduces the Multi-Scale Spatial-Frequency Collaborative Detection Transformer (MSF-DETR) for enhanced small target detection in side-scan sonar images. The novel algorithm improves accuracy and reduces computational load in marine exploration.

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Area of Science:

Marine exploration and engineering
Underwater acoustics
Computer vision

Background:

Side-scan sonar imaging is crucial for underwater target detection.
Small target detection in sonar images presents challenges like limited feature utilization and high computational complexity.
Existing methods struggle with multi-scale feature fusion and efficient processing.

Purpose of the Study:

To develop an advanced algorithm for accurate and efficient small target detection in side-scan sonar images.
To address limitations in frequency domain feature utilization, multi-scale fusion, and computational complexity.
To introduce the Multi-Scale Spatial-Frequency Collaborative Detection Transformer (MSF-DETR).

Main Methods:

Developed a novel end-to-end algorithm, MSF-DETR, for small target detection.
Integrated a Multi-domain Adaptive Spatial-frequency Network (MASNet) backbone for dual-domain feature extraction.
Employed a Hierarchical Multi-scale Adaptive Feature Pyramid Network and an Efficient Sparse Attention Transformer Encoder.

Main Results:

MSF-DETR achieved 78.5% mAP50 and 38.5% mAP50-95 on the SSST-3K dataset.
Demonstrated significant improvements over the baseline RT-DETR (2.8% and 3.3% respectively).
Reduced computational complexity by 12.0% and achieved a 71.2 FPS inference speed.

Conclusions:

MSF-DETR offers an effective solution for small target detection in challenging marine environments.
The algorithm significantly advances underwater sonar image processing capabilities.
The study highlights the potential of collaborative spatial-frequency processing for sonar image analysis.