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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...

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Detalles Bibliográficos
Autores principales: Zhu, Deyan, Tang, Junwei, Fu, Xiaoxuan, Geng, Yuanchao, Su, Jingqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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
Descripción
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.