基于卷积稀疏表示的多频GPR图像融合,以提高道路检测.
Liang Fang1, Feng Yang1, Yuanjing Fang1
1School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China.
Journal of imaging
|January 27, 2026
概括
这项研究引入了使用卷积稀疏表示 (CSR) 的多频地面透雷达 (GPR) 数据融合技术. 该方法通过将低频透与高频分辨率相结合,提高了GPR图像清晰度.
科学领域:
- 地质物理学 地质物理学
- 信号处理 信号处理
- 雷达技术 雷达技术的使用
背景情况:
- 单频地面穿透雷达 (GPR) 在穿透深度和分辨率方面面临限制.
- 挑战包括狭窄的带宽和声干扰,阻碍了详细的地下成像.
研究的目的:
- 开发一种先进的多频GPR数据融合技术.
- 克服单频GPR系统中固有的权衡.
- 为了提高GPR图像的清晰度和可解释性.
主要方法:
- 实施了用于多频GPR信号融合的卷积散散表示 (CSR) 框架.
- 在聚变之前,空间注册的多频GPR信号.
- 从模拟的高清GPR数据中导出卷积字典.
主要成果:
- 基于CSR的融合方法显著超过了传统方法,如加权平均,PCA和2D波段.
- 使用信息,平均梯度,相互信息和视觉信息忠实性的评估证实了优越性.
- 成功地将低频的深度透与高频的高分辨率相结合.
结论:
- 开发的CSR技术有效地协同使用多频 GPR 数据.
- 这种方法大大提高了GPR图像的清晰度和可解释性,用于地下分析.
- 为克服传统GPR系统的局限性提供了一个有希望的解决方案.
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