CML 3D Image/Video Quality Assessment

Paper Title


Yu-Hsun Lin and Ja-Ling Wu, "Quality Assessment of Stereoscopic 3D Image Compression by Binocular Integration Behaviors", IEEE Trans. on Image Processing, Vol.23, No. 4, 2014 PDF

Authors


Yu-Hsun Lin (Ph.D. Candidate, Dept. of GINM, NTU) webpage
Mail: lymanblue[at]cmlab.csie.ntu.edu.tw

Prof. Ja-Ling Wu (Professor, Dept. of CSIE and GINM, NTU) webpage
Mail: wjl[at]cmlab.csie.ntu.edu.tw

Abstract


The objective approaches of 3D image quality assessment play a key role for the development of compression standards and various 3D multimedia applications. The quality assessment of 3D images faces more new challenges, such as asymmetric stereo compression, depth perception, and virtual view synthesis, than its 2D counterparts. Moreover, the widely used 2D image quality metrics (e.g. PSNR and SSIM) cannot be directly applied to deal with these newly introduced challenges. This statement can be verified by the low correlation between the computed objective measures and the subjectively measured mean opinion scores (MOS), when 3D images are the tested targets. In order to meet these newly introduced challenges, in this work, besides traditional 2D image metrics, the binocular integration behaviors - the Binocular Combination and the Binocular Frequency Integration (BFI), are utilized as the bases for measuring the quality of stereoscopic 3D images. The effectiveness of the proposed metrics is verified by conducting subjective evaluations on publicly available stereoscopic image databases. Experimental results show that significant consistency could be reached between the measured MOS and the proposed metrics, in which the correlation coefficient between them can go up to 0.88. Furthermore, we found that the proposed metrics can also address the quality assessment of the synthesized color-plusdepth 3D images well. Therefore, it is our belief that the binocular integration behaviors are important factors in the development of objective quality assessment for 3D images.

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(If you use these resources in your research, please reference our paper)

FI-PSNR (Frequency-Integrated PSNR):
The Matlab codes are the same for the following 2 sources.
- Source 1: MATLAB Code in IEEEXplore Multimedia Material (file name: tip-lin-2302686-mm.zip) link
- Source 2: MATLAB Code in CML link

CML 3D IQA Database (only for academic research) Download
- Password Request link
(If the script is not working, please contact the author: lymanblue[at]gmail.com)
Other FI-Metrics (coming soon)