智能系统学报2026，Vol.21Issue(1)：60-71,12.DOI:10.11992/tis.202505014
基于边缘增强和多尺度特征融合的遥感图像船舰检测
Ship detection in remote sensing images using edge enhancement and multi-scale feature fusion
摘要
Abstract
Ship objects in remote sensing images exhibit large scale variation,dense distribution,and arbitrary orienta-tion.In particular,the low contrast between ships and the ocean background,along with blurred boundaries between ad-jacent ships,poses greater challenges for detection.To address these issues,a model based on edge enhancement and multi-scale feature fusion for ship detection in remote sensing images was proposed.Firstly,a high-frequency feature enhancement module was designed to improve the ability of the model to capture fine details.Furthermore,an edge-guided multi-scale feature fusion method was proposed to mitigate the loss of edge information on low-level during propagation.Finally,a lightweight oriented detection head was constructed to reduce the params of the model Experi-mental results show that the improved model improves 3.6 and 2.1 percentage points of mAP50 on the ShipRSImageN-et dataset and the HRSC2016 Dataset,compared to the YOLO1 l-obb model,effectively improves the accuracy of ship detection in remote sensing images.关键词
遥感图像/船舰检测/高频特征/边缘增强/多尺度/特征融合/轻量化检测头/YOLOKey words
remote sensing image/ship detection/high-frequency feature/edge enhancement/multi-scale/feature fu-sion/lightweight detection head/YOLO分类
信息技术与安全科学引用本文复制引用
王德文,宋学帅,李成浩,赵文清..基于边缘增强和多尺度特征融合的遥感图像船舰检测[J].智能系统学报,2026,21(1):60-71,12.基金项目
国家自然科学基金项目(62371188). （62371188）
