LI Bin, LI Xiuhong, Askar Hamdulla. Infrared Small Target Tracking Based on Super-resolution and Online Detection DSST[J]. Infrared Technology , 2022, 44(7): 659-666.
Citation: LI Bin, LI Xiuhong, Askar Hamdulla. Infrared Small Target Tracking Based on Super-resolution and Online Detection DSST[J]. Infrared Technology , 2022, 44(7): 659-666.

Infrared Small Target Tracking Based on Super-resolution and Online Detection DSST

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  • Received Date: April 24, 2021
  • Revised Date: June 03, 2022
  • Research on infrared small targets is crucial in the areas of military guidance and early warning and detection of border spy UAVs. In this paper, a small target tracking algorithm based on super-resolution enhancement and online detection DSST is proposed for small target tracking research. First, the original image is updated based on the integrated infrared image features of the super-resolution reconstruction algorithm to enhance the dim target. In addition, the enhanced image is used as the input for the online detection DSST algorithm to perform response mapping and estimate the target position. The experimental results show that the accuracy of the proposed algorithm is high compared with those of several new algorithms.
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    WU Wencheng, ASKAR Hamdulla. Infrared small target tracking algorithm based on online ensemble learning[J]. Journal of Shanxi University: Natural Science Edition, 2019, 42(4): 755-761. https://www.cnki.com.cn/Article/CJFDTOTAL-SXDR201904006.htm
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