Ship wake extraction and detection from infrared remote sensing images

被引:0
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作者
Cheng Y. [1 ]
Yu X. [1 ]
Qian W. [1 ]
Qian Y. [1 ]
机构
[1] School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing
关键词
Curvature filter; Dot-Curve; Remote sensing infrared; Wake characteristics;
D O I
10.3788/IRLA20210844
中图分类号
学科分类号
摘要
In infrared remote sensing images with low or medium spatial resolution, the number of pixels occupied by ships on the sea is very small, and the geometric shape and specific texture structure of the target are difficult to obtain. In order to improve the detection limit signal to clutter ratio, the ship wake feature with linear feature was taken as the detection element, which was mathematically characterized. The Dot-Curve detection system was established innovatively. Based on the two-dimensional curvature filtering, the ship detection and wake feature extraction were carried out preliminarily. The feature set was established, from which a number of features with large difference from the background interference items, including wake gray variance, positive and negative gray slope on both sides of the wake, wake linearity and the distance from the hull detection results, were selected to identify the detection results of the candidate targets, remove interference items and extract targets. The results show that after target identification, the ship false detection rate in different bands of infrared images is reduced to less than 8.40%, and the detection rate is improved to at least 94.53%. The ship detection algorithm combines the physical and image characteristics of the wake, which is suitable for many scenes and bands. The algorithm is refined and effective, the physical laws are clear, and the samples needed are few. Copyright ©2022 Infrared and Laser Engineering. All rights reserved.
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  • [1] Li Bo, Application and development trend of infrared stealth technology [J], Chinese Optics, 6, 6, pp. 818-823, (2013)
  • [2] Xu Man, Qiu Su, Jin Weiqi, Radon transform detection method for underwater moving target based on water surface characteristic wave, Acta Optica Sinica, 39, 10, (2019)
  • [3] Lu Jianbin, Contrast feature extraction method for large ship wake image, Ship Science and Technology, 40, 8A, pp. 19-21, (2018)
  • [4] Zou Na, Tian Jinwen, Research on multi feature fusion infrared ship wake detection, Computer Science, 45, 11, pp. 172-175, (2018)
  • [5] Wang Chunzhe, An Junshe, Jiang Xiujie, Et al., Region proposal optimization algorithm based on convolutional neural networks, Chinese Optics, 12, 6, pp. 1348-1361, (2019)
  • [6] Cheng Yuanyuan, Research and application of ship wake detection method based on UAV hyperspectral image, (2020)
  • [7] Xu Fang, Liu Jinghong, Sun Hui, Et al., Research progress on vessel detection using optical remote sensing image, Optics and Precision Engineering, 29, 4, pp. 916-931, (2021)
  • [8] Zhang Yu, Yuan Zhenyu, Wang Hua, Study of optical remote sensing of ship wakes and wake bubbles, Ocean Technology, 29, 3, pp. 82-86, (2010)
  • [9] Jonathan Colen, Kolomeisky Eugene B., Kelvin-Froude wake patterns of a traveling pressure disturbance, European Journal of Mechanics B-Fluids, 85, pp. 400-412, (2021)
  • [10] Jin Fangyuan, Wang Yunying, Guo Yuanyuan, Et al., A method for calculating IR emissivity of ship turbulent trailing wake, Infrared and Laser Engineering, 47, 5, (2018)