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SSIM-Based Coarse-Grain Scalable Video Coding.
- Source :
-
IEEE Transactions on Broadcasting . Jun2015, Vol. 61 Issue 2, p210-221. 12p. - Publication Year :
- 2015
-
Abstract
- We propose an improved coarse-grain scalable video coding (SVC) approach based on the structural similarity (SSIM) index as the visual quality criterion, aiming at maximizing the overall coding performance constrained by user-defined quality weightings for all scalable layers. First, we develop an interlayer rate-SSIM dependency model, by investigating bit rate and SSIM relationships between different layers. Second, a reduced-reference SSIM-Q model and a Laplacian R-Q model are introduced for SVC, by incorporating the characteristics of hierarchical prediction structure in each layer. Third, based on the user-defined weightings and the proposed models, we design a rate-distortion optimization approach to adaptively adjust Lagrange multipliers for all layers to maximize the overall rate-SSIM performance of the scalable encoder. Experiments with multiple layers, different layer weightings, and various videos demonstrate that the proposed framework can achieve better rate-SSIM performance than single layer optimization method, and provide better coding efficiency as compared to the conventional SVC scheme. Subjective tests further demonstrate the benefits of the proposed scheme. [ABSTRACT FROM AUTHOR]
- Subjects :
- *VIDEO coding
*VIDEO codecs
*LAPLACIAN matrices
*GRAPH theory
*LAGRANGE equations
Subjects
Details
- Language :
- English
- ISSN :
- 00189316
- Volume :
- 61
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Broadcasting
- Publication Type :
- Academic Journal
- Accession number :
- 103139013
- Full Text :
- https://doi.org/10.1109/TBC.2015.2424012