Interested Small Target Detection Method Based on Improved SSD for Synthetic Aperture Sonar Image

LI Bao-qi; HUANG Hai-ning; LIU Ji-yuan; LIU Zheng-jun; WEI Lin-zhe

doi:10.12263/DZXB.20220925

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Interested Small Target Detection Method Based on Improved SSD for Synthetic Aperture Sonar Image

PAPERS | 更新时间：2025-12-11

- Interested Small Target Detection Method Based on Improved SSD for Synthetic Aperture Sonar Image
- ACTA ELECTRONICA SINICA Vol. 52, Issue 3, Pages: 762-771(2024)
- 作者机构：
  
  1.中国科学院声学研究所, 北京 100190
  2.中国科学院先进水下信息技术重点实验室, 北京 100190
  3.中国科学院大学, 北京 100049
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20220925
  CLC： TP391
- Received：05 August 2022，
  
  Revised：2023-02-27，
  
  Published：25 March 2024
- 稿件说明：
移动端阅览
李宝奇,黄海宁,刘纪元,等.基于改进SSD的合成孔径声纳图像感兴趣小目标检测方法[J].电子学报,2024,52(03):762-771.

LI Bao-qi, HUANG Hai-ning, LIU Ji-yuan, et al.Interested Small Target Detection Method Based on Improved SSD for Synthetic Aperture Sonar Image[J].Acta Electronica Sinica, 2024, 52(03): 762-771.
李宝奇,黄海宁,刘纪元,等.基于改进SSD的合成孔径声纳图像感兴趣小目标检测方法[J].电子学报,2024,52(03):762-771. DOI：10.12263/DZXB.20220925

LI Bao-qi, HUANG Hai-ning, LIU Ji-yuan, et al.Interested Small Target Detection Method Based on Improved SSD for Synthetic Aperture Sonar Image[J].Acta Electronica Sinica, 2024, 52(03): 762-771. DOI：10.12263/DZXB.20220925

摘要

轻量化目标检测模型SSD-MV3（Single Shot Detection-MobileNet V3）因输入图像尺寸限制无法直接检测高分辨率大尺寸合成孔径声纳（Synthetic Aperture Sonar， SAS）图像中感兴趣小目标.为此，本文提出了一种新的目标检测方法HRSSD（High Resolution Single Shot Detection），该方法通过冗余切割确保SSD-MV3输入图像尺寸的规范以及感兴趣小目标的完整，并利用二次非极大值抑制保证检测结果的唯一.此外，提出了一种尺度、空间和通道注意力机制联合的特征提取模块，并利用该模块重新设计了SSD-MV3的基础网络和附加特征提取网络，记作SSD-MV3P（Single Shot Detection-MobileNet V3 Pro），使得SSD-MV3P能更有效的感知感兴趣小目标特征信息.实验结果表明，在感兴趣小目标检测数据集SST（Sonar Small Targets）上，SSD-MV3P的平均检测精度（mean Average Precision， mAP）比SSD-MV3提升4.39%.HRSSD实现了高分辨率大尺寸SAS图像感兴趣小目标的检测，并且保证了同一位置上检测结果的完整性和唯一性.

Abstract

The efficient object detection model SSD-MV3 (Single Shot Detection-MobileNet V3) cannot directly detect the interested small targets in high-resolution SAS (Synthetic Aperture Sonar) images due to the input image size limit. To this end

this paper proposes a novel object detection method

HRSSD (High Resolution Single Shot Detection)

which ensures the specification of SSD-MV3 input image size and the integrity of the interested small targets through redundant cutting algorithm

and guarantees the unique detection result by using secondary non-maximum suppression. Furthermore

an improved feature block with a combination of scale

space and channel attention mechanism is proposed

and the basic network and additional feature network of SSD-MV3 are redesigned as SSD-MV3P (Single Shot Detection-MobileNet V3 Pro). Thus

SSD-MV3P can more effectively perceive the feature information of interested small targets. The experimental results show that the mAP (mean Average Precision) of SSD-MV3P is 4.39% higher than that of SSD-MV3 on the interested small target detection dataset SST (Sonar Small Target). HRSSD realizes the detection of the interested small targets in high-resolution SAS images

and ensures the integrity and uniqueness of the detection result at the same location.

关键词

Keywords

references

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