Compact Polarimetric SAR Ship Detection Based on Deformation Convolution and Data Augmentation

Compact Polarimetric (CP) SAR has a larger imaging bandwidth compared to full-polarimetric SAR and more polarization information than dual-polarimetric SAR, which has significant potential in maritime ship detection. The non-uniform scale of ship targets and complex backgrounds present detection cha...

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Bibliographic Details
Main Authors: Zhang, Futing, Yin, Qiang, Zhang, Fan, Ma, Fei, Zhou, Yongsheng
Format: Conference Proceeding
Language:English
Subjects:
Attention mechanisms
CBAM
Compact Polarimetric
Data Augmentation
Deformable Convolutions
Feature extraction
Imaging
Neck
Object detection
Reliability
Satellites
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Summary:Compact Polarimetric (CP) SAR has a larger imaging bandwidth compared to full-polarimetric SAR and more polarization information than dual-polarimetric SAR, which has significant potential in maritime ship detection. The non-uniform scale of ship targets and complex backgrounds present detection challenges. This paper proposes an improvement to YOLOv8 by employing deformable convolutions in the backbone network and adding attention mechanisms in the network neck. Deformable convolutions excel at extracting multi-scale features of ships with strong expressive capability, while attention mechanisms suppress the learning of background features. The paper utilizes a CP SAR dataset constructed by using high-information-content SPAN images and augments the dataset. In comparison with the experimental results of the standard YOLOv8 model, our method demonstrates an improvement of 3.2% in recall, 3.6% in precision, and 1.5% in mAP. The results indicate the effectiveness of our approach in the task of ship detection using CP SAR.
ISSN:2153-7003
DOI:10.1109/IGARSS53475.2024.10640762