LAUSR

The estimation of the sea background from maritime infrared video sequences is necessary for target detection. It is challenging to obtain an accurate background model when the scene is a complex and fluctuating sea surface. However, the amplitude spectrum sequences at each frequency point of the pure seawater frames in the Fourier domain are more stable than the gray value sequences of each pixel in the spatial domain. Thus, the background is modeled with a Gaussian distribution in the Fourier domain with the mean and variance adapted over time. In addition, the sea background dynamics are introduced by the variance of the amplitude spectrum sequence, and the dynamic Gaussian discriminant coefficient is set up for each frequency point. Two target discrimination flags are presented based on the background dynamics and Gaussian discriminant process to extract the target more accurately. Furthermore, the entropy filter in the Fourier domain is designed to enhance the target and suppress the sea clutter. The proposed method is successfully tested over several maritime infrared video sequences and has better detection effects compared with several existing state-of-the-art methods.