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- Title
A Two-Stage SAR Image Generation Algorithm Based on GAN with Reinforced Constraint Filtering and Compensation Techniques.
- Authors
Liu, Ming; Wang, Hongchen; Chen, Shichao; Tao, Mingliang; Wei, Jingbiao
- Abstract
Generative adversarial network (GAN) can generate diverse and high-resolution images for data augmentation. However, when GAN is applied to the synthetic aperture radar (SAR) dataset, the generated categories are not of the same quality. The unrealistic category will affect the performance of the subsequent automatic target recognition (ATR). To overcome the problem, we propose a reinforced constraint filtering with compensation afterwards GAN (RCFCA-GAN) algorithm to generate SAR images. The proposed algorithm includes two stages. We focus on improving the quality of easily generated categories in Stage 1. Then, we record the categories that are hard to generate and compensate by using traditional augmentation methods in Stage 2. Thus, the overall quality of the generated images is improved. We conduct experiments on the moving and stationary target acquisition and recognition (MSTAR) dataset. Recognition accuracy and Fréchet inception distance (FID) acquired by the proposed algorithm indicate its effectiveness.
- Subjects
AUTOMATIC target recognition; GENERATIVE adversarial networks; SYNTHETIC aperture radar; DATA augmentation; ALGORITHMS; FILTERS &; filtration; X chromosome
- Publication
Remote Sensing, 2024, Vol 16, Issue 11, p1963
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs16111963