Deep Image Prior Amplitude SAR Image Anonymization

Abstract

This paper presents an extensive evaluation of the Deep Image Prior (DIP) technique for image inpainting on Synthetic Aperture Radar (SAR) images. SAR images are gaining popularity in various applications, but there may be a need to conceal certain regions of them. Image inpainting provides a solution for this. However, not all inpainting techniques are designed to work on SAR images. Some are intended for use on photographs, while others have to be specifically trained on top of a huge set of images. In this work, we evaluate the performance of the DIP technique that is capable of addressing these challenges: it can adapt to the image under analysis including SAR imagery; it does not require any training. Our results demonstrate that the DIP method achieves great performance in terms of objective and semantic metrics. This indicates that the DIP method is a promising approach for inpainting SAR images, and can provide high-quality results that meet the requirements of various applications.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 27, 2023
Source ID
10.3390/rs15153750

Entities

People

  • Edoardo Daniele Cannas
  • Edward J. Delp
  • Paolo Bestagini
  • Sara Mandelli
  • Stefano Tubaro

Organizations

  • Air Force Research Laboratory
  • Defense Advanced Research Projects Agency
  • Polytechnic University of Milan
  • Purdue University

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Image Processing and Computer Vision.
  • Optical Fiber Sensing and Electromagnetic Propagation.