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Generalized matched filters and univariate Neyman-Pearson detectors for image target detection

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1 Author(s)
Caprari, Robert S. ; Defence Sci. & Technol. Organ., Salisbury, SA, Australia

I derive two-stage, statistically suboptimal target detectors for images. The first, or transformation, stage is a “generalized matched filter” (GMF) that linearly transforms the input image. I propose three rational signal-to-noise-ratio criteria whose maximization yields the three GMFs. The second, or detection, stage is a univariate “Neyman-Pearson detector” (NPD), which executes a pointwise likelihood ratio test on the GMF transformed images. Experiments on infrared and synthetic-aperture radar imagery compare GMF/NPDs with several established detectors

Published in:

Information Theory, IEEE Transactions on  (Volume:46 ,  Issue: 5 )