Paper
15 September 1998 Performance modeling of feature-based classification in SAR imagery
Michael Boshra, Bir Bhanu
Author Affiliations +
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 Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Boshra and Bir Bhanu "Performance modeling of feature-based classification in SAR imagery", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); https://doi.org/10.1117/12.321868
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Data modeling

Performance modeling

Scattering

3D modeling

Distortion

Synthetic aperture radar

Target recognition

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