Infrared Small Target Detection Based on Spatial-Temporal Enhancement Using Quaternion Discrete Cosine Transform

Infrared small target detection plays an important role in the infrared search and track system. However, infrared small target images often suffer from low contrast. In this paper, we propose an infrared small target detection method that improves the target contrast and suppresses background clutters based on spatial-temporal enhancement using the quaternion discrete cosine transform (QDCT). The proposed method is twofold: 1) we propose to detect the infrared small target by constructing the quaternion feature map for infrared images. The quaternion integrates four feature maps, including the kurtosis feature, two directional feature maps extracted by steerable filtering in spatial domain and motion feature in the temporal domain. 2) Then the quaternion is input into QDCT, and the saliency maps of each feature channel can be obtained by sign function processing. The final detection result is obtained by inverse QDCT to the quaternion. Compared to several state-of-the-art algorithms, the proposed method has a lower false alarm rate when the same positive detection rate is achieved.