Subjective and Objective Quality Assessment for Stereoscopic Image Retargeting

Abstract

Binocular stereoscopic image retargeting (SIR) aims to adjust 3D images into target aspect ratios. In recent years, various SIR methods have been proposed, but there are few researches on visual quality assessment. As a consequence, we construct a benchmark stereoscopic image retargeting quality assessment database (NBU-SIRQA), which contains 720 stereoscopic retargeted images generated by eight representative SIR operators. Subjective test is conducted to obtain the mean opinion score (MOS) for each stereoscopic retargeted image. Additionally, we propose an objective SIRQA metric based on grid deformation and information loss (GDIL). The main idea of GDIL is to decompose the SIR operator into two transformations: monocular image retargeting transformation and viewpoint transformation. In each transformation, grid deformation and information loss are extracted simultaneously to represent image quality and 3D perception quality. Experimental results validated on our established NBU-SIRQA database show the superiority of our metric in measuring the quality of stereoscopic retargeted images over the existing approaches.