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SAR Image Super-Resolution based on Artificial Intelligence

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

High-resolution synthetic aperture radar (SAR) image can provide detailed information of the target, which is a benefit for improving the performance of the following interpretation application. However, the higher the resolution, the more complex the system and the higher the cost. A new challenge is how to obtain high-resolution target images from medium resolution images, by using new technology, such as artificial intelligence. In this paper, a new method is proposed to improve the resolution based on the SRGAN-SSIM. Since SRGAN is developed for nature image super-resolution, which results in a poor performance for SAR image, pre-processing is implemented. A modified Non-Local Means (NLM) is adopted for speckle noise suppression. Then, SRGAN based net is used for super-resolution, and the loss function is optimized according to the SSIM. Finally, the method is verified by Terra-SAR images.

Original languageEnglish
Title of host publicationIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4643-4646
Number of pages4
ISBN (Electronic)9781665427920
DOIs
StatePublished - 2022
Event2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 - Kuala Lumpur, Malaysia
Duration: 17 Jul 202222 Jul 2022

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2022-July

Conference

Conference2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Country/TerritoryMalaysia
CityKuala Lumpur
Period17/07/2222/07/22

Keywords

  • AI
  • Image
  • SRGAN
  • Super-resolution (SR)
  • Synthetic aperture radar (SAR)

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