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The infrared small target detection technology has a wide range of applications in maritime defense warning and maritime border reconnaissance, especially in the maritime and sky scenes for detecting potential terrorist attacks and monitoring maritime borders. However, due to the weak nature of infrared targets and the presence of background interferences such as wave reflections and islands in maritime scenes, targets are easily submerged in the background, making small infrared targets hard to detect. We propose the multidimensional information fusion network(MIFNet) that can learn more information from limited data and achieve more accurate target segmentation. The multidimensional information fusion module calculates semantic information through the attention mechanism and fuses it with detailed information and edge information, enabling the network to achieve more accurate target position detection and avoid detecting one target as multiple ones, especially in high-precision scenes such as maritime target detection, thus effectively improving the accuracy and reliability of detection. Moreover, experiments on our constructed dataset for small infrared targets in maritime scenes demonstrate that our algorithm has advantages over other state-of-the-art algorithms, with an IoU of 79.09%, nIoU of 79.43%, F1 score of 87.88%, and AuC of 95.96%. [ABSTRACT FROM AUTHOR]

Abstract: To reduce the influences of the heavy clutter on infrared small target detection, a new background suppression algorithm is presented in this paper which depends on fusion of two different filters. The Nucleus Similarity Degree (NSD) of each pixel is analyzed first, then morphological Open filter which favors point target enhancement and the Nucleus Similar Pixels Bilateral Filter (NSPBF) which favors background prediction are fused. The complex background suppression and target enhancement can be accomplished more effectively by the fusion. Experimental results indicates that the method is efficient for background suppression under the condition of heavy clutter. [Copyright &y& Elsevier]