An objective quality assessment metric for stereoscopic images based on three-dimensional structure tensor
Duan Fen-fan · Journal of Optoelectronics·laser · 2014
Stereoscopic image quality assessment is an effective way to evaluate the performance of stereoscopic video system.However,how to utilize human visual characteristics in quality assessment is still an issue.In this paper,considering the characteristics of gradient structure tensor in image feature description,an objective stereoscopic image quality assessment method based on three-dimensional(3D)structure tensor is proposed.To be more specific,we obtain the horizontal,vertical and inter-view gradient information for each pixel in the original and distorted stereoscopic images,and construct the 3Dstructure tensor.Then,the corresponding eigenvalues and eigenvectors are extracted from the 3Dstructure tensor.Finally,according to the eigenvalues and the eigenvectors,the values of objective assessment between the original and distorted stereoscopic images are predicted.Experimental results demonstrate that compared with other methods,the overall Pearson linear correlation coefficient(PLCC)and the Spearman rank order correlation coefficient(SROCC)indicators reach 0.92,the Kendall rank-order correlation coefficient(KROCC)indicator reaches 0.80,and the root mean squared error(RMSE)indicator is approximately6.00,which indicates that the proposed method can achieve higher prediction accuracy.