Improved aircraft detection algorithm in arbitrary direction of color remote sensing image based on anchor-free method

DU Yan-ling; XU Xin; WANG Li-li; GAO Jing-xia; HUANG Dong-mei

doi:10.37188/CJLCD.2022-0218

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Improved aircraft detection algorithm in arbitrary direction of color remote sensing image based on anchor-free method

Image Processing | 更新时间：2023-03-15

- Improved aircraft detection algorithm in arbitrary direction of color remote sensing image based on anchor-free method
- Chinese Journal of Liquid Crystals and Displays Vol. 38, Issue 3, Pages: 409-417(2023)
- 作者机构：
  
  1.上海海洋大学信息学院，上海 201306
  2.自然资源部东海信息中心，上海 200136
  3.上海电力大学，上海 201306
- 作者简介：
- 基金信息：
  
  Youth program of National Natural Science Foundation of China(41906179);Capacity building project of local colleges and universities of Shanghai Municipal Commission of science and technology(20020500700);Shanghai Education Development Fund Project(AASH2004)
- DOI：10.37188/CJLCD.2022-0218
  CLC：
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DU Yan-ling, XU Xin, WANG Li-li, et al. Improved aircraft detection algorithm in arbitrary direction of color remote sensing image based on anchor-free method. [J]. Chinese Journal of Liquid Crystals and Displays 38(3):409-417(2023)
DOI：

DU Yan-ling, XU Xin, WANG Li-li, et al. Improved aircraft detection algorithm in arbitrary direction of color remote sensing image based on anchor-free method. [J]. Chinese Journal of Liquid Crystals and Displays 38(3):409-417(2023) DOI： 10.37188/CJLCD.2022-0218.

摘要

针对彩色遥感图像上飞机目标体积小、分布密集、背景复杂导致的检测精度低问题，提出了一种改进无锚点的彩色遥感图像任意方向飞机目标检测算法。采用BBAVectors为基准模型，以ResNet50为主干网进行特征提取，在特征金字塔网络FPN后增加一条自上而下的路径扩展网络PANet模块，缩短信息路径并用低层级准确位置信息增强特征金字塔。其次，引入注意力机制CBAM模块，通过抑制噪声和突出目标特征，实现复杂环境下的飞机目标检测精度的提升。在DOTA数据集上分别进行消融实验和对比实验，并使用DOTA_devkit对数据集分别进行0.5以及1倍比例的裁切，提高模型的检测精度。改进后的模型在彩色遥感图像测试数据集上的检测精度达到了90.35%。相较于原模型，检测精度提升了0.82%。实验结果表明，该方法在彩色遥感图像中的飞机检测任务中具有更好的检测效果。

Abstract

Aiming at the problem of low detection accuracy caused by small volume， dense distribution and complex background of aircraft targets in the color remote sensing images， an improved aircraft target detection algorithm in any direction of the color remote sensing images based on anchor-free is proposed. Using BBAVectors as the benchmark model and ResNet50 as the backbone network for feature extraction. after the feature pyramid network （FPN）， a top-down path augmentation network （PANet） module is added to shorten the information path and enhance the feature pyramid with low-level accurate location information. Secondly， the attention mechanism convolutional block attention module（CBAM） is introduced to improve the accuracy of aircraft target detection in complex environment by suppressing the noise and highlighting target characteristics. Ablation experiments and comparative experiments are conducted on DOTA data sets， and DOTA_ Devkit is used to cut the data set by 0.5 and 1 times respectively to improve the detection accuracy of the model. The detection accuracy of the improved model on the color remote sensing image test data set reaches 90.35%. Compared with the original model， the detection accuracy is improved by 0.82%. The experimental results show that this method has better detection effect in the aircraft detection task in color remote sensing images.

关键词

飞机目标检测任意方向无锚点路径扩展注意力机制

Keywords

aircraft target detectionin any directionanchor freepath augmentationattention mechanism

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