Paper
29 April 2010 A method to simulate synthetic aperture sonar images with parameterized autocorrelation functions
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Abstract
An approach to simulate synthetic aperture sonar (SAS) images with known autocorrelation functions (ACF) and single-point statistics is presented. ACF models for generating textures with and without periodicities are defined and explained. Simulated textures of these models are compared visually with real SAS image textures. Distortion and degradation of the synthetic textures are examined for various simulation parameter choices.
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J. Tory Cobb, K. Clint Slatton, and Jose Principe "A method to simulate synthetic aperture sonar images with parameterized autocorrelation functions", Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 76640Y (29 April 2010); https://doi.org/10.1117/12.851110
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Distortion

Point spread functions

Computer simulations

Image processing

Statistical analysis

Gaussian filters

Statistical modeling

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