欢迎访问《计测技术》杂志网站

无控制点场景下基于多运动目标的卫星视频稳像算法

Satellite video stabilization algorithm based on multiple moving targets in no⁃control⁃point scenarios

中文摘要:

为了解决无控制点场景下现有卫星视频稳像算法失效的问题，提出了一种基于多运动目标的卫星视频稳像算法，该算法构建了目标检测、轨迹平滑和范数优化的框架，将多目标卡尔曼滤波、rlowess轨迹平滑与L1?L2范数优化相结合，最终实现卫星视频稳像。利用海上多目标舰船观测数据集开展实验，验证该算法的有效性，结果表明基于多运动目标的卫星视频稳像算法在X、Y 方向上的稳像误差均不超过0. 3个像素。本研究填补了无控制点场景下卫星视频稳像的技术空白，具有重要的工程应用价值。

英文摘要:

To address the failure of existing satellite video stabilization algorithms in no?control?point scenarios, a satellite video stabilization algorithm based on multiple moving targets is proposed. This algorithm constructs a framework that integrates target detection, trajectory smoothing, and norm optimization by combining multi?target Kalman filtering, rlowess trajectory smoothing, and L1?L2 norm optimization, ultimately achieving satellite video stabilization. Experiments were conducted using a maritime multi?target ship observation dataset. The results validate the effectiveness of the algo? rithm, showing that the stabilization error of the proposed algorithm can be controlled within 0.3 pixels in both the X and Y directions. This study fills the technical gap in satellite video stabilization in no?control?point scenarios and has broad and significant engineering application value.

作者	单位
李睿瑄	（钱学森空间技术实验室，北京 100094）
李峰*	（钱学森空间技术实验室，北京 100094）
辛蕾	（钱学森空间技术实验室，北京 100094）
杨雪	（钱学森空间技术实验室，北京 100094）
张南	（钱学森空间技术实验室，北京 100094）

中文关键词: 无控制点场景卫星视频稳像多运动目标亚像元级卡尔曼滤波 rlowess平滑 L1⁃L2范数优化

英文关键词:no⁃control⁃point scenarios satellite video stabilization multiple moving targets sub⁃pixel level Kalman filtering rlowess smoothing L1⁃L2 norm optimization

基金项目:

DOI：10.11823/j.issn.1674-5795.2024.02.08

引用本文：李睿瑄,李峰*,辛蕾,杨雪,张南.无控制点场景下基于多运动目标的卫星视频稳像算法[J].计测技术,2024,(2):.

关闭