A New Error Concealment Algorithm Based on Directional Texture Synthesis

Article Preview

Abstract:

In this paper, we propose a novel directional texture synthesis based error concealment algorithm to recover damaged video images. It uses the confidence level and structure information to calculate the priority of patch, which contributes to improve the ability to select the best matching block when the damaged area is very large. The JM86 model of H.264 standard is used to evaluate the algorithm. And experimental results show that our algorithm achieved a better image reconstruction results than the improved Multi-directional texture interpolation algorithm, with 1.2 to 1.4dB gain in PSNR and 0.5 percent to 1 percent gain in SSIM.

You have full access to the following eBook

Info:

Periodical:

Pages:

309-314

Citation:

Online since:

September 2012

Export:

Share:

Citation:

[1] W. -F. Qin, Research of Error Controls And Concealment Technology Based on H. 264/AVC, Ph. D dissertation, Sichuan University, Chendu, (2005).

Google Scholar

[2] Y. Wang, Q. -F. Zhu, and Leonard SHAW. Maximally Smooth Image Recovery in Transform Coding, IEEE Transactions on Communications. 41 (1993) 1544-1551.

DOI: 10.1109/26.237889

Google Scholar

[3] X. -H. Sun, H. -N. Wang, New Spatial Error Concealment Method Based on Multi-texture Direction, Journal of Chinese Computer Systems. 30 (2009) 2264-2267.

Google Scholar

[4] Q. Li, J. -M. He, and Y. Ming, Error Concealment Algorithm Based on Edge Detection And Directional Weight for H. 264 Intra Frame, Application Research of Computers. 27 (2010) 4798-4800.

Google Scholar

[5] X. -H. Wang, F. -H. Li, and Y. -Z. Huang, Improved Spatial Error Concealment Method Based on Multi-texture Direction, Journal of Chinese Computer Systems. 32 (2011) 1452-1455.

Google Scholar

[6] L. Wei, X. -H. Chen, Algorithm of Image Inpainting Based on Texture Orientation, Computer Applications. 28 (2008) 2315-2317.

DOI: 10.3724/sp.j.1087.2008.02315

Google Scholar

[7] Y. -L. Lin, J. -H. Zhao, and X. -F. Zhu, Y. -J. Hu, Image Inpainting Technology Based on Image Decomposition, Computer Engineering. 36 (2010) 187-192.

Google Scholar