Abstract: Stereoscopic 3D (S3D) image retargeting aims to adjust aspect ratio of S3D images. To objectively and accurately assess the quality of different retargeted S3D images, a retargeted S3D image quality assessment database was constructed. Firstly, 45 original images were retargeted by eight representative retargeting algorithms with two retargeting scales to generate 720 retargeted S3D images. Then, the subjective quality evaluation score of each retargeted image was obtained via subjective testing. Finally, the subjective scores were converted to MOS (Mean Opinion Score) values. Based on all above, an objective quality assessment method was proposed for retargeted S3D images. In this method, three types of features including depth perception, visual comfort and image quality of left and right views were extracted to calculate the retargeted S3D image quality with the use of support vector regression prediction. Experimental results on the proposed database show that the proposed method has the Pearson linear correlation coefficient and the Spearman rank-order correlation coefficient higher than 0.82 and 0.81 respectively, demonstrating its superiority in retargeted S3D image visual quality assessment.

Key words: quality assessment, image database, stereoscopic 3D image retargeting, depth perception, visual comfort

摘要： 三维（S3D）图像重定向技术的作用是调整S3D图像的宽高比。为准确和客观地衡量三维重定向图像的视觉质量，建立了一个S3D重定向图像质量评价数据库。首先，使用八种具有代表性的三维重定向算法对45幅原始图像按两种重定向尺度进行分辨率调整，共生成720幅三维重定向图像；然后，每幅重定向图像通过主观测试，得到相应的主观打分值；最后，对主观分数进行处理，得到平均主观意见分（MOS）值。在此基础上，提出一种三维重定向图像客观质量评价方法，即通过提取S3D重定向图像的深度感特征、视觉舒适度特征和左右视点的图像质量特征，使用支持向量回归预测得到S3D重定向图像的视觉质量。在提出的数据库上进行测试可以得知，所提方法的Pearson线性相关系数高于0.82，Spearman等级系数高于0.81，表明其能有效预测S3D重定向图像的视觉质量。

关键词: 质量评价, 图像数据库, 三维图像重定向, 深度感, 舒适度