Abstract
Stereo video has been widely applied in various video systems in recent years. Therefore, objective stereo video quality metric (SVQM) is highly necessary for improving the watching experience. However, due to the high dimensional data in stereo video, existing metrics have some defects in accuracy and robustness. Based on the characteristics of stereo video, this paper considers the coexistence and interaction of multi-dimensional information in stereo video and proposes an SVQM based on multi-dimensional analysis (MDA-SVQM). Specifically, a temporal-view joint decomposition (TVJD) model is established by analyzing and comparing correlation in different dimensions and adaptively decomposes stereo group of frames (sGoF) into different subbands. Then, according to the generation mechanism and physical meaning of each subband, histogram-based and LOID-based features are extracted for high and low frequency subband, respectively, and sGoF quality is obtained by regression. Finally, the weight of each sGoF is calculated by spatial-temporal energy weighting (STEW) model, and final stereo video quality is obtained by weighted summation of all sGoF qualities. Experiments on two stereo video databases demonstrate that TVJD and STEW adopted in MDA-SVQM are convincible, and the overall performance of MDA-SVQM is better than several existing SVQMs.
Highlights
Stereo video can provide a more immersive watching experience for viewers, so stereo video systems have been widely used in various fields [1,2]
The NBU-3DV database is utilized to train for stereo group of frames (sGoF) quality prediction model
Stereo video contains both stereo information generated by left and right views and spatial-temporal information generated by video, which makes it difficult to describe in the design of quality metric
Summary
Stereo video can provide a more immersive watching experience for viewers, so stereo video systems have been widely used in various fields [1,2]. Stereo video quality evaluation can be divided into subjective evaluation and objective evaluation. Subjective evaluation is implemented by evaluate the quality of stereo video according to the watching experience of viewers. Because human eyes are the terminal receivers of stereo video, subjective evaluation is considered to be best in reliability and accuracy. Such an evaluation process is time-consuming and laborious. The objective metric which can evaluate stereo video quality automatically is highly demanded [5]
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