MCL-3D: a database for stereoscopic image quality assessment using 2D-image-plus-depth source

TL;DR

The paper introduces MCL-3D, a comprehensive stereoscopic image quality assessment database with diverse distortions, and benchmarks existing quality metrics using this dataset to facilitate future research.

Contribution

It presents the MCL-3D database with 693 stereoscopic image pairs and evaluates the performance of various 2D and 3D quality metrics on this new dataset.

Findings

Benchmarking results of quality metrics on MCL-3D

Diverse distortions affect stereoscopic image quality

Public availability of the MCL-3D database

Abstract

A new stereoscopic image quality assessment database rendered using the 2D-image-plus-depth source, called MCL-3D, is described and the performance benchmarking of several known 2D and 3D image quality metrics using the MCL-3D database is presented in this work. Nine image-plus-depth sources are first selected, and a depth image-based rendering (DIBR) technique is used to render stereoscopic image pairs. Distortions applied to either the texture image or the depth image before stereoscopic image rendering include: Gaussian blur, additive white noise, down-sampling blur, JPEG and JPEG-2000 (JP2K) compression and transmission error. Furthermore, the distortion caused by imperfect rendering is also examined. The MCL-3D database contains 693 stereoscopic image pairs, where one third of them are of resolution 1024x728 and two thirds are of resolution 1920x1080. The pair-wise comparison was adopted in the subjective test for user friendliness, and the Mean Opinion Score (MOS) can be computed accordingly. Finally, we evaluate the performance of several 2D and 3D image quality metrics applied to MCL-3D. All texture images, depth images, rendered image pairs in MCL-3D and their MOS values obtained in the subjective test are available to the public (http://mcl.usc.edu/mcl-3d-database/) for future research and development.