Journal Article

Automatic target recognition of synthetic aperture radar (SAR) images based on optimal selection of Zernike moments features

Amoon, Mehdi, Rezai-rad, Gholam-ali

2014

نظرة عامة

In the present study, a new algorithm for automatic target detection (ATR) in synthetic aperture radar (SAR) images has been proposed. First, moving and stationary target acquisition and recognition image chips have been segmented and then passed to a number of preprocessing stages such as histogram equalisation, position and size normalisation. Second, the feature extraction based on Zernike moments (ZMs) having linear transformation invariance properties and robustness in the presence of the noise has been introduced for the first time. Third, a genetic algorithm-based feature selection and a support vector machine classifier have been presented to select the optimal feature subset of ZMs for decreasing the computational complexity. Experimental results demonstrate the efficiency of the proposed approach in target recognition of SAR imagery. The authors obtained results show that just a small amount of ZMs features is sufficient to achieve the recognition rates that rival other established methods, and so ZMs features can be regarded as a powerful discriminatory feature for automatic target recognition applications relevant to SAR imagery. Furthermore, it can be observed that the classifier performs fairly well until the signal-to-noise ratio falls beneath 5 dB for noisy images.

• الناشر: The Institution of Engineering and Technology,Institution of Engineering and Technology,John Wiley & Sons, Inc,Wiley
• موضوع: Algorithms / Applied sciences / ATR / automatic target detection / Automatic target recognition / automatic target recognition applications / Classifiers / computational complexity / Detection, estimation, filtering, equalization, prediction / Exact sciences and technology / Feature extraction / genetic algorithm-based feature selection / genetic algorithms / histogram equalisation / image recognition / Imagery / Information, signal and communications theory / invariance robustness / linear transformation invariance properties / Miscellaneous / moving target acquisition / noisy images / Object recognition / optimal feature subset / optimal selection / Optimization / Pattern recognition / position normalisation / preprocessing stages / radar computing / radar imaging / recognition image chips / SAR images / Signal and communications theory / Signal processing / Signal representation. Spectral analysis / Signal, noise / signal-to-noise ratio / size normalisation / stationary target acquisition / support vector machine classifler / support vector machines / SVM / Synthetic aperture radar / synthetic aperture radar images / Telecommunications and information theory / Zernike moments features / ZM features