电子学报2024，Vol.52Issue(3)：762-771,10.DOI:10.12263/DZXB.20220925
基于改进SSD的合成孔径声纳图像感兴趣小目标检测方法
Interested Small Target Detection Method Based on Improved SSD for Synthetic Aperture Sonar Image
摘要
Abstract
The efficient object detection model SSD-MV3(Single Shot Detection-MobileNet V3)cannot directly de-tect 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 interest-ed 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
合成孔径声纳/感兴趣小目标检测/轻量化目标检测模型/注意力机制/二次非极大值抑制Key words
synthetic aperture sonar/interested small target detection/efficient object detection model/attention mechanism/secondary non maximum suppression分类
信息技术与安全科学引用本文复制引用
李宝奇,黄海宁,刘纪元,刘正君,韦琳哲..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(3):762-771,10.基金项目
国家自然科学基金(No.11904386) National Natural Science Foundation of China(No.11904386) （No.11904386）
