Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Performance modeling of feature-based classification in SAR imagery

[+] Author Affiliations
Michael Boshra, Bir Bhanu

Univ. of California/Riverside (USA)

Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, 661 (September 15, 1998); doi:10.1117/12.321868
Text Size: A A A
From Conference Volume 3370

  • Algorithms for Synthetic Aperture Radar Imagery V
  • Edmund G. Zelnio
  • Orlando, FL | April 13, 1998

abstract

We present a novel method for modeling the performance of a vote-based approach for target classification in SAR imagery. In this approach, the geometric locations of the scattering centers are used to represent 2D model views of a 3D target for a specific sensor under a given viewing condition (azimuth, depression and squint angles). Performance of such an approach is modeled in the presence of data uncertainty, occlusion, and clutter. The proposed method captures the structural similarity between model views, which plays an important role in determining the classification performance. In particular, performance would improve if the model views are dissimilar and vice versa. The method consists of the following steps. In the first step, given a bound on data uncertainty, model similarity is determined by finding feature correspondence in the space of relative translations between each pair of model views. In the second step, statistical analysis is carried out in the vote, occlusion and clutter space, in order to determine the probability of misclassifying each model view. In the third step, the misclassification probability is averaged for all model views to estimate the probability-of-correct- identification (PCI) plot as a function of occlusion and clutter rates. Validity of the method is demonstrated by comparing predicted PCI plots with ones that are obtained experimentally. Results are presented using both XPATCH and MSTAR SAR data.

© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Michael Boshra and Bir Bhanu
"Performance modeling of feature-based classification in SAR imagery", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, 661 (September 15, 1998); doi:10.1117/12.321868; http://dx.doi.org/10.1117/12.321868


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.