Stereoscopic image quality evaluation is widely employed in the field of stereo image processing. Based on accurate resolution of wavelet-packet, a novel algorithm for no-reference stereoscopic image quality assessment is proposed. It evaluates stereo image quality via fusion map, which consists of cyclopean map and difference map. First, the stereo image pair is decomposed by wavelet-packet, and afterwards the decomposed left and right views are fused to obtain cyclopean map and difference map based on the principle of binocular rivalry and binocular suppression. Then, Natural Scene Statistics (NSS) features and information entropy are extracted on the fusion map; besides, the structural similarity feature is extracted by taking into account the internal relations between the left and right views. Finally, the Support Vector Regression (SVR) is used to establish model between the perception features and subjective scores, which can predict the objective evaluation score. The experimental results on LIVE 3D image databases show that the proposed algorithm has high consistency with the subjective evaluation results, and it outperforms state-of-the-art stereoscopic image quality assessment algorithms and is in accordance with the human visual perception characteristics.