Volume 38, Number 6, December 2020
|Page(s)||1345 - 1351|
|Published online||02 February 2021|
Target Detection of UAV Aerial Image Based on Rotational Invariant Depth Denoising Automatic Encoder
CNPC Tubular Goods Research Institute, Xi'an 710077, China
2 School of Civil Aviation, Northwestern Polytechnical University, Xi'an 710072, China
3 China National Aviation Fuel Pengzhou Pipeline Transportation Company Limited, Chengdu 610202, China
The method of using unmanned aerial vehicle (UAV) to obtain aerial image information of target scene has the characteristics of wide coverage, strong mobility and high efficiency, which is widely used in urban traffic monitoring, vehicle detection, oil pipeline inspection, regional survey and other aspects. Aiming at the difficulties of the object to be detected in the process of aerial image object detection, such as multiple orientations, small image pixel size and UAV body vibration interference, a novel aerial image object detection model based on the rotation-invariant deep denoising auto encoder is proposed in this paper. Firstly, the interest region of the aerial image is extracted by the selective search method, and the radial gradient of interest region is calculated. Then, the rotation invariant feature descriptor is obtained from the radial gradient feature, and the noise in the original data is filtered out by the deep denoising automatic encoder and the deep feature of the feature descriptors is extracted. Finally, the experimental results show that this method can achieve high accuracy for aerial image target detection and has good rotation invariance.
Key words: UAV aerial image / target detection / deep denoising automatic encoder / rotation-invariant / model / simulation experiment
关键字 : 无人机航空影像 / 目标检测 / 深度去噪自动编码器 / 旋转不变性
© 2020 Journal of Northwestern Polytechnical University. All rights reserved.
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