一种基于多尺度局部梯度对比的适应性红外小目标检测融合算法,用于远程传感
Juan Chen1,2, Lin Qiu1,2, Zhencai Zhu1,2
1Innovation Academy for Microsatellites of Chinese Academy of Sciences, Shanghai 200120, China.
Micromachines
|August 26, 2023
概括
本研究引入了一种使用红外探测器在复杂背景中检测小目标的新方法. 这种方法提高了检测准确度,并减少了云和建筑等具有挑战性的环境中的错误报警.
科学领域:
- 航空航天工程 航空航天工程
- 信号处理 信号处理
- 计算机视觉 计算机视觉
背景情况:
- 红外 (IR) 探测器对于航空航天领域的小目标探测至关重要,但面临着诸如云和地面杂乱等复杂背景的挑战.
- 由于背景特征不分化,传统方法在低信号与杂乱比率 (SCR) 和高错误报警率方面扎.
研究的目的:
- 开发一个强大的检测和跟踪方法,用于在复杂的背景下,低SCR的小目标.
- 为了提高小目标,背景噪音和高亮度边缘之间的区别.
主要方法:
- 利用复杂性差异作为在混乱环境中检测的先决条件.
- 采用了空间域过的联合算法,并改进了局部对比度.
- 引入了渐变均的新定义,以增强目标对比度.
主要成果:
- 通过结合空间过和改善局部对比度,实现了显著区域检测.
- 证明了目标对比度和从背景元素中区分的改进.
- 该方法支持并行计算,以实现高效的处理.
结论:
- 拟议的灵活的核聚变战略大大提高了在具有挑战性的条件下小型目标的检测.
- 与传统算法相比,该方法提供了优越的信号对杂乱比增益 (SCRG) 和背景抑制因子 (BSF).
- 这种方法对于航空航天应用中快速准确地检测小目标是有效的.
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