| 李 睿,李亚洲,赵建文,周卫波.基于多尺度特征融合的地理测绘影像目标检测[J].林业调查规划,2024,49(4):188-194 |
| 基于多尺度特征融合的地理测绘影像目标检测 |
| Target Detection of Geographic Mapping Image Based onMulti-scale Feature Fusion |
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| DOI： |
| 中文关键词: 目标检测 地理测绘影像 边缘信息 多尺度特征 深度卷积网络 检测耗时 |
| 英文关键词: target detection geographic mapping image edge information multi-scale feature deep
convolution network detection time |
| 基金项目:山东省电力公司科技项目(520632220002). |
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| 摘要点击次数: 354 |
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| 中文摘要: |
| 为了提高对地理测绘目标的检测准确度,设计了基于多尺度特征融合的地理测绘影像目标检
测方法。初步提取地理测绘遥感影像的边缘信息,并计算其边缘密度与边缘分布情况,通过增强边
缘信息实现对遥感影像的预处理,得到更明确的影像边缘信息;利用梯度采样法建立下降金字塔影
像,并融合多尺度特征,为后续的目标提取提供更准确、特征更明显的信息;根据特征融合结果,采用
深度卷积网络实现对地理测绘影像目标的有效检测。结果表明,应用该方法,检测结果的准确率、召
回率和F1分数数值均较高,检测耗时也维持在较低的数值范围,该方法可明显提高目标检测效果。 |
| 英文摘要: |
| In order to improve the detection accuracy of geographic mapping targets, a target detection
method of geographic mapping images based on multi-scale feature fusion was designed. The edge information
of the remote sensing image of geographical mapping was preliminarily extracted, and its edge
density and edge distribution were calculated. Through enhancing the edge information, the remote sensing
image was preprocessed to obtain more clear image edge information. Gradient sampling method was
used to establish the descending pyramid image to provide more accurate and distinct information for subsequent
target extraction by integrating multi-scale feature. According to the feature fusion results, the
deep convolution network was used to effectively detect the geographic mapping image objects. The experimental
results showed that the accuracy, recall and F1 score of the detection results were high after the
application of this method, and the detection time was also maintained in a lower numerical range, indicating
that the method significantly improved the detection effect for targets. |
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