A Novel Multi-Frequency Coordinated Module for SAR Ship Detection
Chenchen Qiao, Fei Shen, Xuejun Wang, Ruixin Wang, Fang Cao, Sixian Zhao, Chang Li
Abstract
Synthetic aperture radar (SAR) ships have rich multi-frequency information, however, existing SAR ship detection methods mostly only consider high-frequency information, ignoring other frequency features and structured relationships. For that, a novel plug-and-play Multi-Frequency Coordinated (MFC) module is developed for SAR ship detection. Specifically, the proposed MFC consists of the two key submodules, i.e., Multi-Frequency Aggregate (MFA) and Frequency Response (FR). First, MFA is used to refine the different frequency feature maps along the channel dimension and Discrete Cosine Transform (DCT) bases to solve the problem of dense multi-target SAR ship detection. Then, FR is introduced to select the one with a better response from multi-frequency and boost the significant features of ship targets and suppress interference of surroundings. Lastly, we develop a YOLOv5s-MFC by embedding the MFC for ship detection. Extensive experiments on three large-scale ship datasets (SSDD, HRSID, and LS-SSDD-v1.0) demonstrate that the proposed YOLOv5s-MFC is superior to state-of-the-art ship detection approaches.