• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Auto-Covariance Analysis for Depth Map Coding


Abstract

Efficient depth map coding is very crucial to the multi-view plus depth (MVD) format of 3-D video representation, as the quality of the synthesized virtual views highly depends on the accuracy of the depth map. Depth map contains smooth area within an object but distinct boundary, and these boundary areas affect the visual quality of synthesized views significantly. In this paper, we characterize the depth map by an auto-covariance analysis to show the locally anisotropic features of depth map. According to the characterization analysis, we propose an efficient depth map coding scheme, in which the directional discrete cosine transforms (DDCT) is adopted to substitute the conventional 2-D DCT to preserve the boundary information and thereby increase the quality of synthesized view. Experimental results show that the proposed scheme achieves better performance than that of conventional DCT with respect to the bitrate savings and rendering quality.


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Cite this article

[IEEE Style]
Lei Liu, Yao Zhao, Chunyu Lin and Huihui Bai, "Auto-Covariance Analysis for Depth Map Coding," KSII Transactions on Internet and Information Systems, vol. 8, no. 9, pp. 3146-3158, 2014. DOI: 10.3837/tiis.2014.09.011

[ACM Style]
Liu, L., Zhao, Y., Lin, C., and Bai, H. 2014. Auto-Covariance Analysis for Depth Map Coding. KSII Transactions on Internet and Information Systems, 8, 9, (2014), 3146-3158. DOI: 10.3837/tiis.2014.09.011