Fast new small-target detection algorithm based on a modified partial differential equation in infrared clutter

To detect and track moving dim targets against the complex cluttered background in IR image sequences is still a difficult problem because the nonstationary structured background clutter usually results in low target detectability and a high probability of false alarm. A new adaptive anisotropic filter based on a modified partial differential equation (AFMPDE) is proposed to detect a small target in such a strong cluttered background. A regularizing operator is employed to adaptively eliminate structured background and simultaneously enhance the target signal. The proposed algorithm's performance is illustrated and compared with the two-dimensional least mean square (TDLMS) adaptive filter on real IR image data. Experimental results demonstrate that the proposed novel method is fast and effective.