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Detection of infrared small target based on background subtraction local contrast measure and Gaussian structural similarity
Infrared (IR) small target detection, especially in a complex background, continues to present challenges in the low false alarm rate and high robustness. In this paper, a background subtraction local contrast measure (BSLCM) and Gaussian structural similarity (GSS) integrated structural model is pr...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361040/ https://www.ncbi.nlm.nih.gov/pubmed/37484242 http://dx.doi.org/10.1016/j.heliyon.2023.e16998 |
Sumario: | Infrared (IR) small target detection, especially in a complex background, continues to present challenges in the low false alarm rate and high robustness. In this paper, a background subtraction local contrast measure (BSLCM) and Gaussian structural similarity (GSS) integrated structural model is proposed to detect IR small target. In the proposed model, BSLCM is used to suppress the complex background and enhance the target. GSS calculation is conducted to eliminate the high-brightened background residual and noise further. To evaluate the performance of the proposed method, real IR sequences and seven state-of-the-art (SOTA) methods were adopted. The results demonstrated that the BSLCM can suppress all types of strong background clutter and enhance the true target effectively. |
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