A new feature extraction scheme for evaluating the complexity of Electromagnetic Environment (EME) is presented based on the generalized S transform and morphological pattern spectrum (MPS) in this study. Firstly, the EME signals were transformed to time-frequency image (TFI) by the generalized S transform, which combines the separate strengths of the short-time Fourier transform and wavelet transforms. Secondly, the MPS, which has been widely used in image processing area, is employed to characterize the TFI of EME signals. We also investigated the influence of structure element (SE) to the MPS. Four types of SE, mean the line SE, square SE, diamond SE and circle SE, are utilized and compared for computing the MPS. EME signals with four complexity degree are simulated to evaluate the effectiveness of the presented method. Experimental results have revealed that the presented feature extraction scheme is an effective tool for discriminating the complexity of EME.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.