Generative Adversarial Network-Based Jitter Distortion Correction for High Resolution Spaceborne Images
Hao Wang, Ying Bo Zhu, Lei Wang, Lei Ma, Jinmeng Wu, Ting Li · 2024
This paper presents a Generative Adversarial Network (GAN)-based jitter distortion correction method for spaceborne images of Time Delay Integration (TDI) Charge-Coupled Device (CCD) camera. This method leverages the advantages of GANs and combines content loss, adversarial loss, and perceptual loss to effectively repair distorted images while preserving image details, which does not rely on jitter information captured by high-frequency attitude sensors, nor depends on the analysis of overlapping areas between different bands in multispectral images. The experimental results show that the proposed method achieves automated correction of geometric distortions and has shown promising restoration results on real distorted images captured by Yaogan-26 satellite and GaoFen satellite, which achieves better results than other blind restoration methods.