Stereo image quality assessment is the basis of perception and is also the foundation of stereo video system design. Since human beings are the final receiver of the images， it is essential that the image quality assessment matches the characteristics of the human visual system (HVS). An algorithm for stereo image quality assessment is proposed based on the basic HVS characteristics such as visual non-linearity， contrast sensitivity， multi-channel model， masking effect， and so on. A five level wavelet decomposition is first performed on the images. The spatial frequency of an image is divided into six bands to vary the spatial frequency of the initial image according to the characteristic of the masking effect. Then the similarity measure for each of the frequency bands is evaluated. According to the contrast sensitivity characteristics， the quality evaluation results of each band are weighted to get the final quality assessment scale. The experimental results show that the proposed algorithm outperforms conventional objective image quality methods， and has good agreement between objective and subjective perception. It may reflect the image quality and stereo sense.