Overview

Infrared small target detection can be classified into data-driven methods and model-driven methods. The data-driven methods rely heavily on computational resources and labeled training samples. In contrast, the model-driven small target detection algorithms typically require fewer computing resources and do not require training samples. Moreover, they are easy to implement on platforms with limited resources and hold great potential for practical implementations The model-driven approaches can be classified into three categories: morphological filtering-drive, human visual system-driven and sparse representation-driven algorithms. 

References

Y. Li, Z. Li, J. Li, J. Yang, A. Siddique, "Robust small infrared target detection using weighted adaptive ring top-hat transformation", Signal Processing, Volume 217, April 2024.