海洋测绘2024，Vol.44Issue(3)：42-46,5.DOI:10.3969/j.issn.1671-3044.2024.03.009
同步码字优化降噪的声纳图像多目标检测方法
Multi-object detection method of sonar image with simultaneous codeword optimization for noise reduction
摘要
Abstract
In order to solve the problem of inaccurate identification of underwater targets due to low resolution and serious noise pollution in undersea side-scan sonar images,this paper proposes a target detection method for underwater sonar images combined with simultaneous codeword optimization for noise reduction.The multiplicative noise in the sonar image is reduced by using simultaneous code word optimization,so that the underwater targets in the image can be better visualized and detected,and the corresponding data set is expanded for the sonar image.Finally,YOLOv7 in the YOLO series,which is suitable for the method in this paper,is used to detect the target objects in the sonar images after noise reduction,and the convolutional block attention module is added to its feature network to enhance the feature extraction of the targets.The analysis of simulation results concludes that the target detection method combining synchronous codeword optimized noise reduction and YOLOv7 can achieve a target confidence of 78%,which is 15%higher compared with the target detection confidence before noise reduction,and can better improve the leakage and false detection for objects with smaller targets.关键词
侧扫声纳图像处理/水下目标特征提取/多目标检测/同步码字优化降噪/YOLOv7目标识别Key words
side-scan sonar image processing/underwater target feature extraction/multi-object detection/simultaneous codeword optimization noise reduction/YOLOv7 target recognition分类
天文与地球科学引用本文复制引用
魏光春,邢传玺,崔晶,董赛蒙..同步码字优化降噪的声纳图像多目标检测方法[J].海洋测绘,2024,44(3):42-46,5.基金项目
国家自然科学基金(61761048) （61761048）
云南省基础研究专项面上项目(202101AT070132). （202101AT070132）
