Using Structural degradation and Parallax for reduced-reference quality assessment of 3D images

Owing to the thriving market of stereoscopic image based applications, efficient and effective 3D image quality assessment (IQA) techniques become colossally required these days. Consequently, we introduce a new reduced-reference (RR) stereoscopic image quality metric to meet this demand, through measuring Structural degradation and Saliency based Parallax compensation Model (SSPM). Experimental results on the LIVE 3D Image Quality Database, including both symmetrically and asymmetrically distorted stereoscopic images in different categories and quality levels, are provided to justify the effectiveness of the proposed SSPM model as compared to some existing progressive and popular stereoscopic IQA approaches. Meanwhile, it deserves broad attentions that only four number pairs, extracted from original image, are required as the key feature to be sent to the receiver terminal, thus making this procedure also efficient.

[1]  Sumohana S. Channappayya,et al.  No- Reference Stereoscopic Image Quality Assessment , 2015 .

[2]  Do-Kyoung Kwon,et al.  Full-reference quality assessment of stereopairs accounting for rivalry , 2013, Signal Process. Image Commun..

[3]  Chaminda T. E. R. Hewage,et al.  Reduced-reference quality metric for 3D depth map transmission , 2010, 2010 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video.

[4]  Alan C. Bovik,et al.  No-Reference Quality Assessment of Natural Stereopairs , 2013, IEEE Transactions on Image Processing.

[5]  Wenjun Zhang,et al.  A new reduced-reference image quality assessment using structural degradation model , 2013, 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013).

[6]  Alan C. Bovik,et al.  Subjective evaluation of stereoscopic image quality , 2013, Signal Process. Image Commun..

[7]  Wenjun Zhang,et al.  An improved full-reference image quality metric based on structure compensation , 2012, Proceedings of The 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference.

[8]  Sumio Yano,et al.  A study of visual fatigue and visual comfort for 3D HDTV/HDTV images , 2002 .

[9]  Wenjun Zhang,et al.  A new no-reference stereoscopic image quality assessment based on ocular dominance theory and degree of parallax , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[10]  Zhou Wang,et al.  Multi-scale structural similarity for image quality assessment , 2003 .

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

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

[13]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[14]  Zhou Wang,et al.  Modern Image Quality Assessment , 2006, Modern Image Quality Assessment.

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

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

[17]  Wenjun Zhang,et al.  No-Reference Stereoscopic IQA Approach: From Nonlinear Effect to Parallax Compensation , 2012, J. Electr. Comput. Eng..

[18]  Zhou Wang,et al.  No-reference perceptual quality assessment of JPEG compressed images , 2002, Proceedings. International Conference on Image Processing.