基于距离约束的改进FCOS遥感图像检测方法

doi:10.3778/j.issn.1002-8331.2205-0478

摘要/Abstract

摘要： 基于深度学习的遥感图像目标检测方法通常难以排除复杂场景下的背景干扰，从而导致检测精度低。为解决该问题，设计了一种基于尺度分层的特征金字塔结构，并提出了一种基于距离约束的中心回归（distance-constraints centerness，DCCN），从而形成了基于距离约束的改进FCOS遥感图像检测方法。基于尺度分层的特征金字塔结构包括高层语义信息激活模块和低层有效特征感知模块，其中高层语义信息模块重构了特征融合阶段对高层特征图的处理方式，提升了特征金字塔顶部区域的语义感知能力，低层有效特征感知模块通过引入通道注意力机制，增强了通道间的信息交互能力。DCCN能够利用预测样本框与真实样本框之间的距离因素作为回归评估条件，提升了预测框的回归效果。在NWPU VHR-10数据集的实验中，该方法的精度达到92.6%，相比于原FCOS方法提升了4.9个百分点，有效改善了遥感图像检测的精度。

关键词: 遥感图像, 目标检测, 中心回归, 注意力机制

Abstract: Remote sensing image object detection method based on deep learning is usually difficult to eliminate background interference in complex scenes, which leads to low detection accuracy. In order to solve this problem, this paper designs a feature pyramid structure based on scale stratification, and proposes a distance-constraints centerness（DCCN）, thus forming an improved FCOS remote sensing image detection method based on distance constraint. The feature pyramid structure based on scale stratification includes high-level semantic information activation module and low-level effective feature perception module. The high-level semantic information module reconstructs the processing method of high-level feature map in the feature fusion stage, and improves the semantic perception ability of the top area of the feature pyramid. The low-level effective feature perception module enhances the information interaction ability between channels by introducing channel attention mechanism. DCCN can use the distance factor between the prediction box and the groundtruth box as the regression evaluation condition to improve the regression effect of the prediction box. In the experiment on NWPU VHR-10 dataset, the accuracy of this method reaches 92.6%, which is 4.9 percentage points higher than that of the original FCOS method, and effectively improves the accuracy of remote sensing image detection.

Key words: remote sensing image, object detection, centerness, attention mechanism

苏树智, 谢玉麒. 基于距离约束的改进FCOS遥感图像检测方法[J]. 计算机工程与应用, 2023, 59(10): 227-235.

SU Shuzhi, XIE Yuqi. Improved FCOS Remote Sensing Image Detection Method Based on Distance Constraint[J]. Computer Engineering and Applications, 2023, 59(10): 227-235.

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