桂林电子科技大学学报2026，Vol.46Issue(2)：121-127,7.DOI:10.16725/j.1673-808X.202471
一种改进型水下声呐图像目标检测算法
An improved target detection algorithm for underwater sonar images
摘要
Abstract
An improved target detection algorithm for underwater sonar images is proposed.The proposed algorithm achieves excel-lent detection performance on underwater sonar images with high noise and incomplete target details.The image enhancement mod-ule GDIP,which is applied in extreme weather,is introduced and improved to SDIP(Sonar DIP)module,and the improved SDIP module is applied to sonar images with remarkable effect,which can adaptively adjust the parameters of the enhancement algorithm to improve the detection accuracy of the model.Meanwhile,a pixel-level enhancement threshold is also added to enhance the image details while suppressing noise amplification,which is also set as an optimizable parameter to be self-adaptively adjusted through model training.The detection model adopts the fusion structure of CNN and Transformer,and construts the more efficient and ad-vanced Layer Normalization(LN)and Feed-forward Neural Network(FFN)structures in the Transformer network based on the DC-Nv3 operator.The internal architecture of the model is optimized,and EC,Hdc,and PC modules are added to enhance the perfor-mance of the model,which is based on the principle of lightweight deep convolution construction to capture local spatial informa-tion,and it has significant effect on underwater sonar images with large noise and serious information loss.The designed experi-ments prove that enhancing the acquisition of spatial information can effectively improve the detection performance of the model for this task.关键词
水下声呐图像/图像增强/深度学习/目标检测/轻量级深度卷积Key words
underwater sonar image/image enhancement/deep learning/target detection/lightweight depth convolution分类
信息技术与安全科学引用本文复制引用
陈名松,黄宇,陈哲..一种改进型水下声呐图像目标检测算法[J].桂林电子科技大学学报,2026,46(2):121-127,7.基金项目
国家自然科学基金(91836301) （91836301）
广西科技基地和人才专项(桂科AD21220098) （桂科AD21220098）
认知无线电与信息处理教育部重点实验室开放基金(CRKL210102) （CRKL210102）
