Paper
15 September 1998 Eigen-MINACE SAR detection filters with improved capacity
Rajesh Shenoy, David P. Casasent
Author Affiliations +
Abstract
Distortion-invariant correlation filters are used to detect and recognition distorted objects in scenes. They are used in a correlator and are thus shift-invariant. We describe a new way to design distortion-invariant correlation filters that ensures good generalization (same performance on training and test sets) and improved capacity (fewer filters that recognize distorted versions of multiple classes of objects). The traditional way of designing correlation filters uses different types of frequency domain preprocessing and linear combination of training images. We show that these different approaches can be implemented in a framework using linear combination of eigen-images of preprocessed training data. Using eigen-domain data is shown to produce filters that generalize better and have large capacity. We show results on SAR data with multiple classes of objects using eigen-MINACE filters.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rajesh Shenoy and David P. Casasent "Eigen-MINACE SAR detection filters with improved capacity", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); https://doi.org/10.1117/12.321848
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Cited by 5 scholarly publications.
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KEYWORDS
Image filtering

Neon

Synthetic aperture radar

Linear filtering

Detection and tracking algorithms

Databases

Target detection

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