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A Linear Approximation Based Method for Noise-Robust and Illumination-Invariant Image Change Detection

机译:基于线性近似的噪声鲁棒和照明不变图像变化检测方法

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Image change detection plays a very important role in real-time video surveillance systems. To deal with the illumination, a category of linear algebra based algorithms were designed in the literature. They have been proved to be effective for surveillance environment with lighting and shadowing. In practice, other than illumination, the detecting process is also influenced by the noises of cameras and reflections. In this paper, analysis is made systemically on the existing linear algebra detectors, showing their intrinsic weakness in case of noises. In order to get less sensitive to noises, a novel method is proposed based on the technique of linear approximation. Theoretical and experimental analysis both show its robustness and high performance for noisy image change detection.
机译:图像变更检测在实时视频监控系统中起着非常重要的作用。 为了处理照明,在文献中设计了一类基于线性代数的算法。 他们已被证明是用照明和阴影的监测环境有效。 在实践中,除了照明之外,检测过程也受摄像机噪声和反射的影响。 本文在现有的线性代数探测器上系统性地进行了分析,显示出在噪声的情况下的内在弱点。 为了对噪声较少,基于线性近似技术提出了一种新方法。 理论和实验分析既显示出嘈杂的图像变化检测的鲁棒性和高性能。

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