• Infrared Technology
  • Vol. 44, Issue 5, 475 (2022)
Xiangsuo FAN1、2、*, Jinlong FAN3, Lianghua WEN1, and Zhiyong XU4
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    DOI: Cite this Article
    FAN Xiangsuo, FAN Jinlong, WEN Lianghua, XU Zhiyong. Infrared Dim-Small Target Detection Based on Improved Spatio-Temporal Filtering[J]. Infrared Technology, 2022, 44(5): 475 Copy Citation Text show less
    References

    [2] Bae T W, Kim Y C, Ahn S H, et al. An efficient two dimensional least mean square based on block statistics for small target detection[J]. Journal of Infrared, Millimeter, and Terahertz Waves, 2009, 30(10): 1092-1101.

    [3] BAI X Z, ZHOU F G, JIN T. Enhancement of dim small target through modified top-hat transformation under the condition of heavy clutter[J]. Signal Processing, 2010, 90(1): 1643-1654.

    [7] Oliver N M, Rosario B, Pentland A P. A Bayesian computer vision system for modeling human interactions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(8): 831-843.

    [8] Bouwmans T, Baf F E, Vachon B. Background modeling using mixture of Gaussians for foreground detection - a survey [J]. Recent Patents on Computer Science, 2008, 1(3): 219-237.

    [10] GUO J, WU Y, DAI Y. Small target detection based on reweighted infrared patch-image model[J]. IET Image Processing, 2018, 12(1): 70-79.

    FAN Xiangsuo, FAN Jinlong, WEN Lianghua, XU Zhiyong. Infrared Dim-Small Target Detection Based on Improved Spatio-Temporal Filtering[J]. Infrared Technology, 2022, 44(5): 475
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