Abstract

The extraction of objects from advanced geospatial intelligence (AGI) products based on synthetic aperture radar (SAR) imagery is complicated by a number of factors. For example, accurate detection of temporal changes represented in two-color multiview (2CMV) AGI products can be challenging because of speckle noise susceptibility and false positives that result from small orientation differences between objects imaged at different times. These cases of apparent motion can result in 2CMV detection, but they obviously differ greatly in terms of significance. In investigating the state-of-the-art in SAR image processing, we have found that differentiating between these two general cases is a problem that has not been well addressed. We propose a framework of methods to address these problems. For the detection of the temporal changes while reducing the number of false positives, we propose using adaptive object intensity and area thresholding in conjunction with relaxed brightness optical flow algorithms that track the motion of objects across time in small regions of interest. The proposed framework for distinguishing between actual motion and misregistration can lead to more accurate and meaningful change detection and improve object extraction from a SAR AGI product. Results demonstrate the ability of our techniques to reduce false positives up to 60%.

Original languageEnglish (US)
Title of host publicationAlgorithms for Synthetic Aperture Radar Imagery XXIV
PublisherSPIE
Volume10201
ISBN (Electronic)9781510609037
DOIs
StatePublished - 2017
EventAlgorithms for Synthetic Aperture Radar Imagery XXIV 2017 - Anaheim, United States
Duration: Apr 13 2017 → …

Other

OtherAlgorithms for Synthetic Aperture Radar Imagery XXIV 2017
CountryUnited States
CityAnaheim
Period4/13/17 → …

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Keywords

  • 2CMV
  • Change detection
  • Optical flow
  • SAR
  • Synthetic aperture radar

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Kanberoglu, B., & Frakes, D. (2017). Extraction of advanced geospatial intelligence (AGI) from commercial synthetic aperture radar imagery. In Algorithms for Synthetic Aperture Radar Imagery XXIV (Vol. 10201). [1020106] SPIE. https://doi.org/10.1117/12.2262359