Ship Target Detection in SAR Imagery Based on Band Recombination and Multi-Scale Feature Enhancement

Abstract

Synthetic aperture radar images have all-weather and all-time capabilities and are widely used in the field of ship target surveillance at sea. However, its detection accuracy is often limited by factors such as complex sea conditions, diverse ship scales, and image noise. Aiming at the problems such as inconsistent scale of ship target detection in SAR images, difficulty in detecting small targets, and interference from complex backgrounds, this paper proposes a ship detection method for SAR images based on band recombination and multi-scale feature enhancement. Firstly, aiming at the problem that the single-channel replication mode adopted by the deep neural network cannot fully extract the ship target information in SAR images, a band recombination method was designed to enhance the ship information in the images. Furthermore, the coordinate channel attention and bottleneck Transformer attention mechanisms are introduced in the backbone part of the network to enhance the network’s representation ability of the target spatial distribution and maintain the global feature modeling ability. Finally, a multi-scale feature enhancement and multi-scale effective feature aggregation module was designed to improve the detection accuracy of multi-scale ships in wide-format images. The experimental results on the LS-SSDD and HRSID datasets show that the average accuracies of the method proposed in this paper reach 78.1% and 94.5% respectively, which are improved by 6.9% and 0.8% compared with the baseline model, and are superior to other advanced algorithms, verifying the effectiveness of the method proposed in this paper. Meanwhile, the algorithm proposed in this paper has also demonstrated good performance in wide-format SAR images of actual large scenes. The method proposed in this paper effectively improves the problems of missed detection and false detection of small-target ships in SAR images of large scenes. At the same time, it enhances the efficiency of rapid and accurate detection in large scenes and can provide reliable technical support for the field of maritime target surveillance.