基于视差空间图的立体图像质量客观评价方法

立体图像质量评价是评价立体视频系统性能的有 效途径,而如何利用人类视觉特性对立体图像质量 进行有效评价是目前的研究难点。本文提出了一种基于视差空间图(DSI) 的立体图像质量客观评价方法。首先, 分别构造原始立体图像和失真立体图像的DSI图；然后,通过三维离散余弦变换(3D-DCT)提取出反映图像质量 和深度感知的特征信息,并采用主成分分析(PCA)进行特征降维,形成立体图像特征信息； 最后,通过支持向量 回归(SVR)建立立体图像特征与主观评价值的关系,从而预测得到立体图像质量的客观评价 值。实验表明, 对于对称立体图像库,Pearson线性相关系数(PLCC)和Spe arman等级相关系数(SROCC)值均达到0.94以上；对于非 对称立体图像库,PLCC和SROCC值分别达到0.94以上。结果表明,本文方法能够很好地预测人眼对立体图像的主观感 知。

An objective stereoscopic image quality assessment method based on disparity space image

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 as sessment is still an issue. In this paper,an objective stereoscopic image quality assessment method based o n disparity space image (DSI) is proposed.In this method,we first construct DSIs from the original and distorted stereoscopic images,respectively. Then,three-dimensional discrete cosine transformation (3D-DCT) and principal c omponent analysis are used to extract the stereoscopic image feature information from the DSIs that reflect the image qual ity and depth perception.Finally,support vector regression (SVR) is performed to predi ct the objective scores of stereoscopic images by establishing the relationship between the stereoscopic image feature information and the subjecti ve scores.Experimental results show that compared with other methods,the Pearson linear correlation coefficien t (PLCC) and Spearman rank-order correlation coefficient (SROCC) indicators r each 0.94on symmetric stereoscopic image database, and the PLCC indicator reaches 0.94and the SROCC indicator reaches 0.91o n asymmetric stereoscopic image database,which indicate the proposed method can achieve higher consistenc y with subjective assessment of stereoscopic images for both symmetric and asymm etric databases.