Improving InSAR Image Quality and Co-Registration through CNN-Based Super-Resolution | IEEE Conference Publication | IEEE Xplore

Improving InSAR Image Quality and Co-Registration through CNN-Based Super-Resolution

Publisher: IEEE

Abstract:

Interferometric Synthetic Aperture Radar (InSAR) is a measuring technology that uses the phase information contained in the images of the Synthetic Aperture Radar (SAR). ...View more

Abstract:

Interferometric Synthetic Aperture Radar (InSAR) is a measuring technology that uses the phase information contained in the images of the Synthetic Aperture Radar (SAR). InSAR has been recognized as a potential method for digital elevation models (DEMs) generation and ground surface deformation measurement. Nonetheless, the quality of InSAR data is influenced by many critical factors. Including image co-registration, interferogram generation, phase unwrapping and geocoding. Image co-registration aims to align two or more images so that the same pixel in each image corresponds to the same point of the target scene. This study proposes a new algorithm for improving Image co-registration and interferogram generation of SAR using learning-based images super-resolution (SR). We show that our approach improves the conventional approaches.
Date of Conference: 12-14 October 2020
Date Added to IEEE Xplore: 28 September 2020
Print ISBN:978-1-7281-3320-1
Print ISSN: 2158-1525
Publisher: IEEE
Conference Location: Seville, Spain

References

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