A human visual system-based 3D video quality metric

Although several 2D quality metrics have been proposed for images and videos, in the case of 3D efforts are only at the initial stages. In this paper, we propose a new full-reference quality metric for 3D content. Our method is modeled around the HVS, fusing the information of both left and right channels, considering color components, the cyclopean views of the two videos and disparity. Performance evaluations showed that our 3D quality metric successfully monitors the degradation of quality caused by several representative types of distortion and it has 86% correlation with the results of subjective evaluations.

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

[2]  Nikolay N. Ponomarenko,et al.  A NEW FULL-REFERENCE QUALITY METRICS BASED ON HVS , 2006 .

[3]  Munchurl Kim,et al.  A perceptual quality assessment metric using temporal complexity and disparity information for stereoscopic video , 2011, 2011 18th IEEE International Conference on Image Processing.

[4]  Marcus Barkowsky,et al.  Video quality assessment: From 2D to 3D — Challenges and future trends , 2010, 2010 IEEE International Conference on Image Processing.

[5]  Karen O. Egiazarian,et al.  Validation of a new full reference metric for quality assessment of mobile 3DTV content , 2011, 2011 19th European Signal Processing Conference.

[6]  Margaret H. Pinson,et al.  A new standardized method for objectively measuring video quality , 2004, IEEE Transactions on Broadcasting.

[7]  Atanas Gotchev,et al.  Novel Stereo-Video Quality Metric , .

[8]  A. Aksay,et al.  Towards compound stereo-video quality metric: a specific encoder-based framework , 2006, 2006 IEEE Southwest Symposium on Image Analysis and Interpretation.

[9]  Sei-Wang Chen,et al.  A stereoscopic content analysis system with visual discomfort-aware , 2012, 2012 International Conference on 3D Imaging (IC3D).

[10]  Leo Grady,et al.  Random Walks for Image Segmentation , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  A. Bovik.  A VISUAL INFORMATION FIDELITY APPROACH TO VIDEO QUALITY ASSESSMENT , 2005 .

[12]  Alan C. Bovik,et al.  Image information and visual quality , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  Alan C. Bovik,et al.  Image information and visual quality , 2006, IEEE Trans. Image Process..

[14]  Attila Barsi,et al.  View synthesis for lightfield displays using region based non-linear image warping , 2012, 2012 International Conference on 3D Imaging (IC3D).

[15]  Junyong You,et al.  PERCEPTUAL QUALITY ASSESSMENT FOR STEREOSCOPIC IMAGES BASED ON 2 D IMAGE QUALITY METRICS AND DISPARITY ANALYSIS , 2010 .

[16]  Xiaobo Li,et al.  Stereo matching using random walks , 2008, 2008 19th International Conference on Pattern Recognition.

[17]  Peter Kauff,et al.  Preserving dynamic range by advanced color histogram matching in stereo vision , 2012, 2012 International Conference on 3D Imaging (IC3D).