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arXiv · 1711.02010

Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR Data

Dimitrios Marmanis·Wei Yao·Fathalrahman Adam·Mihai Datcu·Peter Reinartz·Konrad Schindler·Jan Dirk Wegner·Uwe Stilla
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Abstract

Very High Spatial Resolution (VHSR) large-scale SAR image databases are still an unresolved issue in the Remote Sensing field. In this work, we propose such a dataset and use it to explore patch-based classification in urban and periurban areas, considering 7 distinct semantic classes. In this context, we investigate the accuracy of large CNN classification models and pre-trained networks for SAR imaging systems. Furthermore, we propose a Generative Adversarial Network (GAN) for SAR image generation and test, whether the synthetic data can actually improve classification accuracy.

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Dimitrios Marmanis, Wei Yao, Fathalrahman Adam, Mihai Datcu, Peter Reinartz, Konrad Schindler, Jan Dirk Wegner, Uwe Stilla. 2017-11-06. Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR Data. https://arxiv.org/abs/1711.02010

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