一种基于注意力机制的红外小目标检测方法
Xiaotian Wang1,2, Ruitao Lu3, Haixia Bi1
1Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
本研究介绍了一种基于注意力的红外小目标检测方法. 该方法通过将自下而上的和自上而下的注意模块与决策反等级集成,提高了复杂背景中的检测准确性和适应性.
科学领域:
- 计算机视觉 计算机视觉
- 信号处理 信号处理
- 人工智能的人工智能
背景情况:
- 人类的视觉注意力在快速红外目标识别和场景适应性方面表现出色.
- 现有的方法难以处理复杂的背景和小型红外线目标.
研究的目的:
- 提出一种基于注意力的红外小目标检测方法.
- 为了提高检测准确度和减少复杂的红外图像中的错误报警.
主要方法:
- 三个模块的方法:自下而上的被动注意力,自上而下的积极注意力和决策反均等化.
- 顶向下模块:高斯形状特征提取和四次元变换用于多维融合.
- 底部向上模块:最佳的快速局部对比度,改进的循环管道过,以及用于候选区域识别和尺寸估计的多尺度拉普拉西亚或高斯过器.
主要成果:
- 与基线方法 (RLCM,ILCM,PQFT,MPCM,ADMD) 相比,提出的方法显示出更高的检测性能.
- 在海,天空和地面杂乱等复杂的背景中有效减少虚假警报.
- 数学证明验证了该方法的有效性.
结论:
- 基于注意力的方法显著提高了红外小目标检测.
- 整合多维特征和强大的过有助于提高准确性和适应性.
- 该方法为现实世界的红外监控应用提供了有前途的解决方案.
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