基于背景减去局部对比度和高斯结构相似性的红外小目标的检测
Deyan Zhu1,2, Junwei Tang1,2, Xiaoxuan Fu1,2
1College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210001, China.
Heliyon
|July 24, 2023
概括
本研究引入了一种用于红外 (IR) 小目标检测的新模型,该模型有效地抑制复杂的背景并提高目标可见性,实现高稳定性和低误报率.
科学领域:
- 计算机视觉 计算机视觉
- 信号处理 信号处理
- 红外成像技术 红外成像技术
背景情况:
- 在复杂的背景下检测红外 (IR) 小目标仍然具有挑战性.
- 实现低误报率和高稳定性对于IR目标检测至关重要.
研究的目的:
- 为增强IR小型目标检测提出一个综合结构模型.
- 在具有挑战性的IR场景中改进背景抑制和目标增强.
主要方法:
- 一个新的模型整合了背景减去局部对比度 (BSLCM) 和高斯结构相似性 (GSS).
- BSLCM用于背景抑制和目标增强.
- 应用GSS以进一步消除残留的背景噪声和亮点.
主要成果:
- 拟议的BSLCM方法有效地抑制各种强烈的背景杂乱.
- 综合模型在提高真正目标方面表现出卓越的表现.
- 在真实IR序列上的实验结果验证了该方法的有效性,与七种最先进的技术相比.
结论:
- 拟议的BSLCM和GSS集成模型为IR小目标检测提供了强大的解决方案.
- 该方法通过有效处理复杂的背景和噪声,显著提高了检测准确度.
- 这种方法有助于推进红外目标识别和监控领域.
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