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GLRT subspace detection of multi-pixel targets with known and unknown spatial parameters in presence of signal-dependent background power

机译:在存在依赖信号的背景功率的情况下,对具有已知和未知空间参数的多像素目标进行GLRT子空间检测

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摘要

The video infrared images captured at long range usually have low brightness and low contrast objects of interest with respect to surrounding background clutter. In this work, we design and analyze two detectors relying on the general likelihood ratio test (GLRT) to detect weak barely discernible multi-pixel objects with known (the first detector) and unknown shape, size and position (the second detector). The derived algorithms combine the multi-pixel matched subspace detector and multi-pixel background-plus-noise power change detector in a unique scheme. The numerical simulations and real experiments show that the first detector considerably outperforms the second one, especially in real-word situation, when the size, shape and position of the object are unknown. Finally, we compare the performances of the proposed detectors to the performances of the recently proposed modified mean subtraction filter and focused correlation (FC) detector. (C) 2016 Elsevier Ltd. All rights reserved.
机译:相对于周围背景杂波,在远距离捕获的视频红外图像通常具有低亮度和低对比度的目标对象。在这项工作中,我们设计和分析了两个检测器,它们依赖于一般似然比测试(GLRT)来检测已知(第一个检测器),形状,大小和位置未知(第二个检测器)的几乎难以分辨的微像素物体。派生算法以独特的方案将多像素匹配子空间检测器和多像素背景加噪声功率变化检测器组合在一起。数值模拟和实际实验表明,第一个检测器明显优于第二个检测器,特别是在实物情况下,当物体的大小,形状和位置未知时。最后,我们将提议的检测器的性能与最近提出的改进的均值减法滤波器和聚焦相关(FC)检测器的性能进行比较。 (C)2016 Elsevier Ltd.保留所有权利。

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