Stereoscopic Image Quality Assessment Method Based on Visual Cell Model
Retinal cells of human visual system (HVS) are used as a medium to receive, transmit and understand binocular information when stereo images are viewed. A new stereo image quality assessment (SIQA) algorithm aiming to imitate retinal cells is proposed. HVS is mimicked by modeling simple cells and complex cells on the basis of the retinal cell characteristics. Binocular fusion view map (BFVM) and binocular cell based disparity map (BCDM) are obtained via the binocular information processing of the simple complex cell models. Based on the multiscale structural similarity (MSSIM) method, the binocular fusion quality assessment (BFQA) and binocular stereo perception assessment (BSPA) are respectively implemented to the original or distorted stereo images. The results of BFQA and BSPA are combined to describe the final quality of stereo images. The experimental results demonstrate that the overall Pearson linear correlation indicator reaches 0.94, Spearman rank order correlation coefficient reaches 0.93, which indicate that the proposed model is well consistent with human perception, and also well predict the stero image quality.