Abstract
To support 3-D video and free-viewpoint video applications, efficient texture videos and depth maps coding should be addressed. In this paper, a novel reversible data hiding scheme is proposed to integrate depth maps into corresponding texture video bitstreams. At the sender end, the depth video bitstream obtained by depth down-sampling and compression is embedded in residual coefficients of corresponding texture video. The data embedding is implemented by the histogram shifting technique. At the receiver end, the depth maps can be retrieved with scalable quality after data extraction, video decoding and texture-based depth reconstruction. Due to the attractive property of reversible data hiding, the texture video bitstream can be perfectly recovered. Experimental results demonstrate that the proposed scheme can achieve better video rendering quality and coding efficiency compared with existing related schemes.
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Notes
- 1.
The independent embedding distortion is calculated by adding an error \(\delta \) to the (i, j)th quantized DCT coefficient in the \(4\times 4\) block using the MSE (Mean Squared Error) measure.
- 2.
In [20], it is suggested that \(\bigtriangleup g_{pq}\) should be calculated in the \(\ell _2\)-norm. Actually, the better reconstructed depth map quality can be obtained if \(\bigtriangleup g_{pq}\) is calculated in the \(\ell _1\)-norm according to our experiments.
- 3.
The color distance in the texture video is calculated between two texture samples which correspond to the missing depth sample and the nearest existing depth sample respectively.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61572452, in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant XDA06030601, and in part by the China Scholarship Council Program under Grant 201506340006.
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Yao, Y., Zhang, W., Yu, N. (2017). Reversible Data Hiding for Texture Videos and Depth Maps Coding with Quality Scalability. In: Shi, Y., Kim, H., Perez-Gonzalez, F., Liu, F. (eds) Digital Forensics and Watermarking. IWDW 2016. Lecture Notes in Computer Science(), vol 10082. Springer, Cham. https://doi.org/10.1007/978-3-319-53465-7_31
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