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An infrared small and dim target detection algorithm based on the mask image

机译:基于掩模图像的红外弱小目标检测算法

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To overcome the affection of heavy clutter and dim target intensity on small target detection, a novel background prediction method is proposed. By combining the mask image and morphological filters, this method can predict the background more precisely and reduce background processing time. Finally, in terms of target detection rates and the procession time per frame, the performance comparison between the proposed method and the Top-hat filtering method is given. The experimental results indicate that this method can enhance the predicted accuracy of background, even in the low SNR (signal-to-noise rate), and is a more preferable and effective way to detect infrared small and dim targets.
机译:为了克服杂波和目标强度大对小目标检测的影响,提出了一种新的背景预测方法。通过将蒙版图像和形态滤镜组合在一起,该方法可以更准确地预测背景并减少背景处理时间。最后,根据目标检测率和每帧的处理时间,给出了所提方法与高帽滤波方法的性能比较。实验结果表明,即使在低SNR(信噪比)的情况下,该方法也可以提高背景的预测精度,是检测红外弱小目标的更有效的方法。

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