Detection and tracking of small infrared motion targets using directional Top-hat algorithm



  • Nguyen Van Thu Institute of Technical Physics, Academy of Military Science and Technology
  • Dang Anh Tuan Institute of Technical Physics, Academy of Military Science and Technology
  • Le Van The Institute of Technical Physics, Academy of Military Science and Technology
  • Nguyen Manh Thang (Corresponding Author) Academy of Military Science and Technology



Small infrared target; Top-hat; Tracking; Reconnaissance.


Small targets are shown on the infrared image as small bright spots, do not carry any characteristics of the target, are difficult to detect, but are the object of reconnaissance and detection equipment, according to long-range tracking. On the basis of the characteristics of the small infrared target and the Top-hat algorithm, a method of using the directional Top-hat filter is proposed to remove the background and enhance the target. Taking advantage of the rich information in consecutive shots of a video and the slow change in position between frames, using the search method from the vicinity of the target position in the previous frame to determine the target, thereby limiting the missing object being tracked. The test results show that the directional Top-hat algorithm is effective in detecting small targets in complex backgrounds, combined with the target recognition algorithm of consecutive frames, allowing precise tracking of the target of interest.


[1]. Rawat, S.S., S.K. Verma, and Y. Kumar, "Review on recent development in infrared small target detection algorithms". Procedia Computer Science. 167: p. 2496-2505, (2020).

[2]. Zhou, F., et al., "Graph-Regularized Laplace Approximation for Detecting Small Infrared Target Against Complex Backgrounds". IEEE Access. 7: p. 85354-85371, (2019).

[3]. Gao, C., et al., "Infrared patch-image model for small target detection in a single image". IEEE Trans Image Process. 22(12): p. 4996-5009, (2013).

[4]. Yang, L., J. Yang, and K. Yang, "Adaptive detection for infrared small target under sea-sky complex background". Electronics Letters. 40(17), (2004).

[5]. Lopez-Alonso, J.M., J. Alda, and E. Bernabeu, "Principal-component characterization of noise for infrared images". Appl Opt. 41(2): p. 320-31, (2002).

[6]. Kim, S., et al., "Small Target Detection Utilizing Robust Methods of the Human Visual System for IRST". Journal of Infrared, Millimeter, and Terahertz Waves. 30(9): p. 994-1011, (2009).

[7]. Fan, J., et al., "IRSDT: A Framework for Infrared Small Target Tracking with Enhanced Detection". Sensors (Basel). 23(9), (2023).

[8]. Bai, Y., et al., "Cross-Connected Bidirectional Pyramid Network for Infrared Small-Dim Target Detection". IEEE Geoscience and Remote Sensing Letters. 19: p. 1-5, (2022).

[9]. Li, Y., et al., "Infrared Small Target Detection Based on Gradient-Intensity Joint Saliency Measure". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 15: p. 7687-7699, (2022).

[10]. Zhang, F., C. Li, and L. Shi, Detecting and tracking dim moving point target in IR image sequence. Infrared Physics & Technology. 46(4): p. 323-328, (2005).

[11]. Deshpande, S., et al., "Max-mean and max-median filters for detection of small targets". SPIE's International Symposium on Optical Science, Engineering, and Instrumentation. Vol. 3809. (1999).

[12]. Bai, X. and F. Zhou, "Analysis of new top-hat transformation and the application for infrared dim small target detection". Pattern Recognition. 43(6): p. 2145-2156, (2010).

[13]. Li, Y., et al., "Infrared maritime dim small target detection based on spatiotemporal cues and directional morphological filtering". Infrared Physics & Technology. 115, (2021).

[14]. Wang, X., et al., "A sparse representation-based method for infrared dim target detection under sea–sky background". Infrared Physics & Technology. 71: p. 347-355, (2015).

[15]. Moradi, S., P. Moallem, and M.F. Sabahi, "Fast and robust small infrared target detection using absolute directional mean difference algorithm". Signal Processing. 177, (2020).



How to Cite

Nguyễn, V. T., Anh Tuấn, T. Lê Văn, and N. Mạnh Thắng. “Detection and Tracking of Small Infrared Motion Targets Using Directional Top-Hat Algorithm”. Journal of Military Science and Technology, vol. 90, no. 90, Oct. 2023, pp. 110-8, doi:10.54939/1859-1043.j.mst.90.2023.110-118.



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