icona researchDIBR-Synthesized image Quality Metric (DSQM)

M.S. Farid, M. Lucenteforte, M. Grangetto, "PERCEPTUAL QUALITY ASSESSMENT OF 3D SYNTHESIZED IMAGES," in Proc. IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, 2017, pp. 505-510.

 

Abstract: Multiview video plus depth (MVD) is the most popular 3D video format where the texture images contain the color information and the depth maps represent the geometry of the scene. The depth maps are exploited to obtain intermediate views to enable 3D-TV and free-viewpoint applications using the depth image based rendering (DIBR) techniques. DIBR is used to get an estimate of the intermediate views but has to cope with depth errors, occlusions, imprecise camera parameters, re-interpolation, to mention a few issues. Therefore, being able to evaluate the true perceptual quality of synthesized images is of paramount importance for a high quality 3D experience. In this paper, we present a novel algorithm to assess the quality of the synthesized images in the absence of the corresponding references. The algorithm uses the original views from which the virtual image is generated to estimate the distortion induced by the DIBR process. In particular, a block-based perceptual feature matching based on signal phase congruency metric is devised to estimate the synthesis distortion. The experiments worked out on standard DIBR synthesized database show that the proposed algorithm achieves high correlation with the subjective ratings and outperforms the existing 3D quality assessment algorithms.


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Experimental Evaluation:

Database used for evaluation: IRCCyN/IVC DIBR Images database

Table 1. Overall performance of DSQM and other 3D-IQA algorithms on IRCCyN/IVC DIBR Images database.

Metric 3DSwIM Tsai PQM Gorley Dragana MW-PSNR SIQE DSQM
PLCC 0.6420 0.4830 0.4709 0.3183 0.7191 0.7378 0.6058 0.7895
SROCC 0.5613 0.4740 0.4869 0.3000 0.6846 0.7070 0.4347 0.7151
RMSE 0.5105 0.5975 0.5877 0.6312 0.4627 0.4494 0.5298 0.4086
MAE 0.4038 0.5051 0.4771 0.4876 0.3370 0.3184 0.4022 0.3067

 

Table 2. Overall performance of DSQM and other 2D-IQA algorithms on IRCCyN/IVC DIBR Images database.

Metric SSIM MS-SSIM PSNR VSNR DSQM
PLCC 0.5639 0.5489 0.4283 0.5145 0.7895
SROCC 0.4687 0.5324 0.4628 0.5051 0.7151
RMSE 0.5499 0.5566 0.6017 0.5709 0.4086

 

Table 3. Performance of DSQM with different block sizes (m,n). Results of the best performing block size are in bold font.

mxn PLCC SROCC RMSE
8x8 0.5062 0.5301 0.5742
16x16 0.6665 0.5998 0.4964
32x32 0.6886 0.6083 0.4828
64x64 0.6962 0.604 0.4779
128x128 0.7895 0.7151 0.4086
256x256 0.7529 0.6749 0.4382
Full Image 0.7261 0.6183 0.4578

 

 

 

Last updated: March 20, 2017