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.