利用主成分背景抑制的红外目标检测

Infrared Target Detection Based on Principal Background Suppression

  • 摘要: 提出了一种基于主成分背景抑制的红外目标检测算法。首先分析了红外成像的时空相关性,采用主成分分析技术分解时域关联信息抑制背景杂波;接着采用空间关联模糊自适应共振神经网络建立时空背景模型检测目标。实验结果显示,该算法能有效地抑制背景突显目标和检测出复杂场景下的红外目标,其F1指标值高达94.2%。

     

    Abstract: A new infrared target detection approach based on principal background suppression is presented.Through analyzing the spatial-temporal correlation of thermal imagery,the principal component analysis technique is utilized to suppress the background clutters.A spatially related fuzzy ART neural network is applied to build the spatial-temporal background models and detect targets by the suppressed frame information.The experiments have been carried out and the results show that the F1 measurement of our proposed approach is up to 94.2%.It is able to suppress background clutters and highlight targets effectively,and it is capable of detecting targets in complex thermal scene accurately.

     

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