Full-Reference 3-D Video Quality Assessment Using Scene Component Statistical Dependencies
| Autor: | Balasubramanyam Appina, Sumohana S. Channappayya |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Image quality
business.industry Covariance matrix Computer science Applied Mathematics media_common.quotation_subject Frame (networking) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Pattern recognition 02 engineering and technology Coherence (statistics) Video quality Signal Processing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Quality (business) Artificial intelligence Electrical and Electronic Engineering business media_common |
| Zdroj: | IEEE Signal Processing Letters. 25:823-827 |
| ISSN: | 1558-2361 1070-9908 |
| DOI: | 10.1109/lsp.2018.2829107 |
| Popis: | In this letter, we present a full-reference (FR) quality assessment algorithm to assess the perceptual quality of natural stereoscopic three-dimensional (S3-D) videos. Toward the end, we rely on an empirical model for the joint statistics of motion and depth subband coefficients of an S3-D video frame. Specifically, we use the recently proposed bivariate generalized Gaussian distribution (BGGD) model for the joint statistics. In this letter, we show that the coherence of the covariance matrix of the BGGD varies in proportion with the perceptual video quality. We compute the coherence scores from the eigenvalues of the covariance matrix to estimate the amount of directional dependency between the motion and depth components. To estimate the overall spatial quality score, we apply off-the-shelf 2-D FR image quality assessment metrics on a frame-by-frame basis on both the views and average the frame wise scores. Finally, we pool the coherence and spatial quality scores to derive the overall quality for the S3-D video. An evaluation of the proposed algorithm on the IRCCYN, WaterlooIVC Phase I, and LFOVIA S3D video databases demonstrates its robust performance. The proposed algorithm is called depth- and motion-based 3-D video quality evaluator. |
| Databáze: | OpenAIRE |
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