计算机工程与应用2025，Vol.61Issue(18)：218-230,13.DOI:10.3778/j.issn.1002-8331.2412-0294
几何变化结合图像增强的航拍图像小目标检测算法
Geometric Transformation Combined with Image Enhancement for Small Target Detection in Aerial Images
摘要
Abstract
Aerial image small target detection is complex,leading to a decline in detection metrics.An algorithm combining geometric transformations and image enhancement is proposed.Using YOLOv8n as the baseline,DCNv2-CA-GEO extracts spatial and channel features in parallel,dynamically adjusting the convolutional and pooling kernels to quickly adapt to geometric changes.SPD-OK-CSP adjusts channel dimensions,capturing fine-grained features and enhancing image quality.Dysample optimizes upsampling,while Dyhead improves detection head performance.The Inner-Wise-MPD-IoU strategy balances sample features and optimizes generalization.Evaluated by mAP@0.5,mAP@0.5:0.95,Precision,and Recall,experiments on VisDrone2021 show improvements of 6.1 percentage points in mAP@0.5,4.4 per-centage points in mAP@0.5:0.95,6.0 percentage points in Precision,and 5.0 percentage points in Recall.On LEVIR-Ship,the improvements are 3.4 percentage points in mAP@0.5,2.2 percentage points in mAP@0.5:0.95,3.1 percentage points in Precision,and 5.3 percentage points in Recall.Generalization tests on VOC2007+2012 demonstrate enhance-ments of 2.0 percentage points in mAP@0.5,4.3 percentage points in mAP@0.5:0.95,1.5 percentage points in Precision,and 3.1 percentage points in Recall,indicating good robustness.关键词
航拍图像/小目标检测/YOLOv8n/SPDConv/Omni-Kernel/DCNv2/DyheadKey words
aerial image/small target detection/YOLOv8n/SPDConv/Omni-Kernel/DCNv2/Dyhead分类
信息技术与安全科学引用本文复制引用
齐向明,李晓龙..几何变化结合图像增强的航拍图像小目标检测算法[J].计算机工程与应用,2025,61(18):218-230,13.基金项目
国家自然科学基金面上项目(62173171). （62173171）
