期刊
REMOTE SENSING
卷 10, 期 10, 页码 -出版社
MDPI
DOI: 10.3390/rs10101597
关键词
dialectical generative adversarial network; image translation; Sentinel-1; TerraSAR-X
类别
资金
- China Scholarship Council [201606030108]
With more and more SAR applications, the demand for enhanced high-quality SAR images has increased considerably. However, high-quality SAR images entail high costs, due to the limitations of current SAR devices and their image processing resources. To improve the quality of SAR images and to reduce the costs of their generation, we propose a Dialectical Generative Adversarial Network (Dialectical GAN) to generate high-quality SAR images. This method is based on the analysis of hierarchical SAR information and the dialectical structure of GAN frameworks. As a demonstration, a typical example will be shown, where a low-resolution SAR image (e.g., a Sentinel-1 image) with large ground coverage is translated into a high-resolution SAR image (e.g., a TerraSAR-X image). A new algorithm is proposed based on a network framework by combining conditional WGAN-GP (Wasserstein Generative Adversarial NetworkGradient Penalty) loss functions and Spatial Gram matrices under the rule of dialectics. Experimental results show that the SAR image translation works very well when we compare the results of our proposed method with the selected traditional methods.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据