针对荒漠背景下红外弱小目标检测问题,提出了一种基于稳定性矩阵恢复和双窗滤波的荒漠红外偏振弱小目标检测方法.分析得出红外偏振Q参量图的背景相似性最高,采用改进型形态学滤波可以增强其背景相关性.检测时将Q图背景看成一个具有低秩特性的矩阵,弱小目标看成是破坏其低秩性的冗余数据,建立稳定性矩阵恢复荒漠背景抑制数学模型,然后对背景抑制结果采用双窗滤波分割出目标,完成检测.实验结果证明了该方法的有效性和稳健性,具有较强的应用价值.

A novel infrared polarization target detection method based on matrix recovery and double window filter, was proposed to remove the complex desert background clutter in the detection of dim and small target. Data analysis demonstrated that similarity of infrared polarization Q image background was the highest. Using morphological filter enhance the similarity of background. Q image background could be seen as a low-rank matrix, dim and small target could be seen as redundancy data which break the similarity of background. So background suppression mathematics model based on stable matrix recovery was build. Detection was completed after double window filter segments targets in background suppression result. Experimental results on real-world infrared polarization images and comparisons with state-of-the-art methods can demonstrate the effectiveness and robustness of the proposed method, and it was suitable for engineering application.