A Reduced Reference Metric for Enhanced 3D Video Perception

Öz

Currently, one of the trending research topics among the researchers assisting to the enhancement of the 3D video services relies on the 3 Dimensional (3D) video Quality of Experience (QoE) prediction metric development process. The researches for this trending topic can be ensured by characterizing the 3D video related features in the most compatible way as possible in this process. Considering this fact, a novel Reduced Reference (RR)) 3D video QoE prediction metric relying on color+depth map 3D video representation is developed in this study. The developed metric utilizes the incorporation of  the Significant Information (SI) in the depth map videos with the Structual Complexity Information (SCI) of their color counterparts. The abstraction filter and Structural SIMilarity Index (SSIM) are exploited for the SI and SCI computations, respectively. Performed subjective experment results are utilized to predict the performance of the developed metric. Observing highly effective results after the performance evaluation process, it can be clearly stated that the developed RR metric is compatible for assisting the advancement of the 3D video services.

Anahtar Kelimeler

• 3D video,depth level,structural complexity

Kaynakça

1. [1] Q. Huynh-Thu, P. Le Callet, and M. Barkowsky, “Video Quality Assessment: From 2D to 3D Challenges and Future Trends,” 17th IEEE International Conference on Image Processing, Hong Kong, 26-29 Sep. 2010. [2] Chaminda T. E. R. Hewage, “Perceptual Quality Driven 3D Video over Networks,” PhD Thesis, Centre for Communication Systems Research Faculty of Engineering and Physical Science, University of Surrey, UK, 2008.[3] C.T.E.R. Hewage, S. T.Worrall, S.Dogan, S. Villette, A. M. Kondoz, “Quality Evaluation of Color Plus Depth May Based 3D Video,” IEEE Journal of Selected Topics in Signal Processing, vol. 3., no. 2, Apr. 2009.[4] G. Nur Yilmaz, “A Depth Perception Evaluation Metric for Immersive 3D Video Services,” 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, 7-9 June 2017.[5] L. Caraffa, J. P. Tarel, P. Charbonnier, “The Guided Bilateral Filter: When the Joint/Cross Bilateral Filter Becomes Robust,” IEEE Transactions on Image Processing, 24 (4), pp 1199-1208, 2015.[6] Chaminda T.E.R. and Martini M. G., “Reduced-Reference Quality Assessment for 3D Video Compression and Transmission,” IEEE Transactions on Consumer Electronics, vol. 57, issue 3, pp. 1185-1193, Aug. 2011.[7] C. Hewage and M.G. Martini, “Reduced-Reference Quality Metric for 3D Depth Map Transmission,” 3DTV Conference, Tampere, Finland, June 2010.[8] C. Hewage and M.G. Martini, “Reduced reference image quality metric for compressed depth map associated with colour plus depth 3D video,” IEEE International Conference on Image Processing (ICIP), Hong Kong, 26-29 Septermber 2010.[9] Chaminda T.E.R., Martini M. G. 2012 “Edge-based Reduced-Reference Quality Metric for 3-D Video Compression and Transmission,” IEEE Journal of Selected Topics in Signal Processing, 5, 471-482.[10] Chaminda T.E.R. and Martini M. G., “Edge-based Reduced-Reference Quality Metric for 3-D Video Compression and Transmission,” IEEE Journal of Selected Topics in Signal Processing, vol. 6, no.5, Sep. 2012.[11] Martini M. G., Chaminda T.E.R., and Villarini B., “Image Quality Assessment Based on Edge-Preservation,” Signal Processing: Image Communication, vol. 27, issue 8, pp. 875-882, Sep. 2012. [12] C. Fehn, “Depth-image-based rendering (DIBR), compression and transmission for a new approach on 3D-TV”, Proc. of SPIE Conf. Stereoscopic Displays and Virtual Reality Systems XI, vol. 5291, pp. 93 – 104, CA, U.S.A., January 2004.[13] JSVM 9.13.1. CVS Server [Online]. Available Telnet: garcon.ient.rwth aachen.de:/cvs/jvt[14]https://www.itu.int/dms_pubrec/itu-r/rec/bt/R-REC-BT.500-13 201201-I!!PDF-E.pdf