Detecting moving objects from ground-based videos is commonly achieved by using background subtraction (BS) techniques. Low-rank matrix decomposition inspires a set of state-of-the-art approaches for this task. It is integrated with structured sparsity regularization to achieve BS in the developed method of low-rank and structured sparse decomposition (LSD). However, when this method is applied to satellite videos where spatial resolution is poor and targets’ contrast to the background is low, its performance is limited as the data no longer fit adequately either the foreground structure or the background model. In this article, we handle these unexplained data explicitly and address the moving target detection from space as one of the pioneering studies. We propose a new technique by extending the decomposition formulation with bounded errors, named Extended LSD (E-LSD). This formulation integrates low-rank background, structured sparse foreground, as well as their residuals in a matrix decomposition problem. Solving this optimization problem is challenging. We provide an effective solution by introducing an alternative treatment and adopting the direct extension of alternating direction method of multipliers (ADMM). The proposed E-LSD was validated on two satellite videos, and the experimental results demonstrate the improvement in background modeling with boosted moving object detection precision over state-of-the-art methods.

中文翻译：

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卫星视频中运动目标检测的误差有界前景和背景建模

从基于地面的视频中检测移动物体通常是通过使用背景减法 (BS) 技术来实现的。低秩矩阵分解激发了一组最先进的方法来完成这项任务。它与结构化稀疏正则化相结合，以在开发的低秩和结构化稀疏分解 (LSD) 方法中实现 BS。然而，当该方法应用于空间分辨率较差且目标与背景对比度较低的卫星视频时，其性能受到限制，因为数据不再充分适合前景结构或背景模型。在本文中，我们明确地处理这些无法解释的数据，并将空间运动目标检测作为开创性研究之一。我们通过扩展有界误差的分解公式提出了一种新技术，命名为扩展 LSD (E-LSD)。该公式在矩阵分解问题中整合了低秩背景、结构化稀疏前景以及它们的残差。解决这个优化问题具有挑战性。我们通过引入替代处理并采用乘法器交替方向直接扩展法 (ADMM) 来提供有效的解决方案。所提出的 E-LSD 在两个卫星视频上得到了验证，实验结果证明了背景建模的改进与最先进的方法相比，运动物体检测精度的提高。我们通过引入替代处理并采用乘法器交替方向直接扩展法 (ADMM) 来提供有效的解决方案。所提出的 E-LSD 在两个卫星视频上得到了验证，实验结果证明了背景建模的改进与最先进的方法相比，运动物体检测精度的提高。我们通过引入替代处理并采用乘法器交替方向直接扩展法 (ADMM) 来提供有效的解决方案。所提出的 E-LSD 在两个卫星视频上得到了验证，实验结果证明了背景建模的改进与最先进的方法相比，运动物体检测精度的提高。