Human Visual System Based Stereoscopic Image Quality Assessment
Hailian Wang · Intelligent Computer and Applications · 2014
With the large- scale development of stereoscopic images,many applications need the ability to quickly and efficiently complete the stereoscopic image quality evaluation for further applications,but the subjective quality assessment is difficult to meet the requirements in terms of efficiency. Therefore,the paper proposes a perceptual quality evaluation algorithm,which combines some characteristics of the human visual system. First,the paper obtains the disparity map,then adjusts the disparity map through the weights in the edge map and the saliency map. After that,the Minkowski pooling is used to integrate the weighted disparity map. Finally,the multiscale strategy is applied to compute the final score. The EPFL database is utilized to validate the proposed metric. Experiment shows that the objective score obtained by the proposed metric and the subjective scores have a high degree of consistency and monotonicity. It is proved that the algorithm to evaluate the perceptual quality of stereoscopic images in this paper is very effective.