Joint spatio-temporal features and sea background prior for infrared dim and small target detection

The detection of dim and small targets in the complex sea background poses new challenges to automatic target search and interception by infrared air-to-air missiles at sea. To solve the problems of low detection rate of dim targets and massive suspected targets caused by the shadow region of clutter on the sea surface, this paper proposes a detection method for dim and small targets with spatio-temporal features and background prior information. Firstly, by combining the ideas of local energy factor and multi-scale patch contrast measure, an improved dim target detection method is proposed, which can effectively enhance the contrast of dim targets and suppress background clutter. Then, according to the grayscale probability distribution difference between the background and the target, a double-Gaussian model is established for the residual background and the target region and a background suppression method based on the spatial prior information is proposed to further suppress the residual background. Finally, a dim target detection method is proposed by combining the above dim target detection, background suppression, and dynamic pipeline filtering methods. The results indicate the average detection rate of the detection method proposed in this study is 91.44%. Also, the average number of false alarms in a single frame is reduced to 9.89, which is more than 80% lower than that of other algorithms.