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26 October 2022 Assessment of preprocessing techniques in a model-based automatic target recognition algorithm for the SAMPLE dataset
Gustavo F. Araujo, Renato Machado, Mats I. Pettersson
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Proceedings Volume 12267, Image and Signal Processing for Remote Sensing XXVIII; 1226705 (2022) https://doi.org/10.1117/12.2636233
Event: SPIE Remote Sensing, 2022, Berlin, Germany
Abstract
This article investigates basic preprocessing techniques to improve classification accuracy in the context of Automatic Target Recognition (ATR) of non-cooperative targets in Synthetic Aperture Radar (SAR) images. Preprocessing techniques are considered in synthetic data providing different inputs to a model-based classification algorithm. Experiments with preprocessing techniques such as area reduction, morphological transformations, and speckle filtering were run using ten target classes of the SAMPLE dataset. The classification is performed in measure data using scattering centers as features. The results reveal that the original image without any preprocessing techniques reached the best classification performance. However, investigations with other classifiers that use different features may benefit from such preprocessing techniques.
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Gustavo F. Araujo, Renato Machado, and Mats I. Pettersson "Assessment of preprocessing techniques in a model-based automatic target recognition algorithm for the SAMPLE dataset", Proc. SPIE 12267, Image and Signal Processing for Remote Sensing XXVIII, 1226705 (26 October 2022); https://doi.org/10.1117/12.2636233
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KEYWORDS
Automatic target recognition
Model-based design
Synthetic aperture radar
Image classification
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