Towards the Standardization of Stereoscopic Video Quality Assessment: An Application for Objective Algorithms

This article describes a Qt-based C++ application for full-reference stereoscopic video quality assessment, which is platform independent and provides a friendly graphical user interface. The stereoscopic video signals used in the application are based on a two-view model, such as the H.264/AVC standard in the Multiview Video Coding (MVC) profile. In addition, several spatial resolutions are available. The application provides objective video quality algorithms, such as PSNR, SSIM, and PW-SSIM and also incorporates a recently published technique for stereoscopic video quality assessment called Disparity Weighting (DW), which comprises the following algorithms: DPSNR, DSSIM and DPW-SSIM. Numerical results corresponding to the performance of the objective measurements, acquired using the proposed application, are presented. The application aims to contribute to the standardization and development of objective algorithms for stereoscopic content. As an open-source tool to be used by the academia and the industry, the application is used to evaluate impairments in stereoscopic video signals, caused by processing, compression and transmission techniques. Journal of ICT, Vol. 2, 247–268. doi: 10.13052/jicts2245-800X.233 c © 2015 River Publishers. All rights reserved. 248 J. Vinı́cius de Miranda Cardoso et al.

[1]  Lina J. Karam,et al.  A MATLAB-based framework for image and video quality evaluation , 2010, 2010 Second International Workshop on Quality of Multimedia Experience (QoMEX).

[2]  Karen O. Egiazarian,et al.  3D-DCT based perceptual quality assessment of stereo video , 2011, 2011 18th IEEE International Conference on Image Processing.

[3]  José Vinícius de Miranda Cardoso,et al.  Effect of visual attention areas on the objective video quality assessment , 2012, WebMedia.

[4]  José Vinícius de Miranda Cardoso,et al.  Objective estimation of 3D video quality: A disparity-based weighting strategy , 2013, 2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB).

[5]  Patrick Le Callet,et al.  Quality Assessment of Stereoscopic Images , 2008, EURASIP J. Image Video Process..

[6]  Jorge Navarro-Ortiz,et al.  Video Tester — A multiple-metric framework for video quality assessment over IP networks , 2012, IEEE international Symposium on Broadband Multimedia Systems and Broadcasting.

[7]  Kwanghoon Sohn,et al.  Depth map quality metric for three-dimensional video , 2009, Electronic Imaging.

[8]  Zhou Wang,et al.  Information Content Weighting for Perceptual Image Quality Assessment , 2011, IEEE Transactions on Image Processing.

[9]  José Vinícius de Miranda Cardoso,et al.  Performance of the objective video quality metrics with perceptual weighting considering first and second order differential operators , 2012, WebMedia.

[10]  Sugato Chakravarty,et al.  Methodology for the subjective assessment of the quality of television pictures , 1995 .

[11]  Narciso García,et al.  NAMA3DS1-COSPAD1: Subjective video quality assessment database on coding conditions introducing freely available high quality 3D stereoscopic sequences , 2012, 2012 Fourth International Workshop on Quality of Multimedia Experience.

[12]  Conrad Sanderson,et al.  Armadillo C++ Linear Algebra Library , 2016 .

[13]  José Vinícius de Miranda Cardoso,et al.  Video Quality Assessment Based on the Effect of the Estimation of the Spatial Perceptual Information , 2012 .

[14]  Rajiv Soundararajan,et al.  Study of Subjective and Objective Quality Assessment of Video , 2010, IEEE Transactions on Image Processing.

[15]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[16]  Siwei Ma,et al.  Stereoscopic video quality assessment model based on spatial-temporal structural information , 2012, 2012 Visual Communications and Image Processing.

[17]  Ingrid Heynderickx,et al.  Studying the added value of visual attention in objective image quality metrics based on eye movement data , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).