Referenced Items are not available for this document.
In this paper, we present an adaptive maximum a posteriori (MAP) error concealment algorithm for dispersively packetized wavelet-coded images. We model the subbands of a wavelet-coded image as Markov random fields, and use the edge characteristics in a particular subband, and regularity properties of subband/wavelet samples across scales, to adapt the potential functions locally. The resulting adaptive MAP estimation gives PSNR advantages of up to 0.7 dB compared to the competing algorithms. The advantage is most evident near the edges, which helps improve the visual quality of the reconstructed images.
Published in:
Image Processing, IEEE Transactions on
(Volume:15
,
Issue:
5
)
Date of Publication: May 2006
- Page(s):
- 1226 - 1235
- ISSN :
- 1057-7149
- INSPEC Accession Number:
- 8937974
- Digital Object Identifier :
- 10.1109/TIP.2005.864166
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 18 April 2006
- Issue Date :
- May 2006
- Sponsored by :
- IEEE Signal Processing Society
- PubMed ID :
- 16671303
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