Paper
14 November 2007 Error concealment method for SPIHT-based image transmission
Xuewen Ding, Zhaoxuan Yang, Jiapeng Wu, Hongxing Zheng, Jihua Cao, Yuting Su
Author Affiliations +
Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67904J (2007) https://doi.org/10.1117/12.749353
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
This paper presents two error concealment (EC) techniques for true 2-D wavelet codec based on set portioning in hierarchal trees (SPIHT), one for the lowest frequency wavelet coefficients (the low-frequency EC) and the other for high frequency coefficients (the high-frequency EC). The low-frequency EC algorithm uses data hiding technique. The low-frequency coefficients, which are taken as the hidden data, are extracted from the compressed bitstream, and embedded back into the same bitstream. The restored hidden data is used to conceal errors. The high-frequency reconstruction is performed in spectral-domain. The damaged high frequency coefficients are predicted through linear interpolation based on inter-subband correlation. Experimental results show that the proposed method achieves good and stable error resilience performance with minimal additional redundancy.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xuewen Ding, Zhaoxuan Yang, Jiapeng Wu, Hongxing Zheng, Jihua Cao, and Yuting Su "Error concealment method for SPIHT-based image transmission", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904J (14 November 2007); https://doi.org/10.1117/12.749353
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data hiding

Error analysis

Wavelets

Image transmission

Wavelet transforms

Image compression

Image quality

Back to Top