Name
Abstract | ||
|---|---|---|
As an alternative implementation of Slepian-Wolf coding, distributed arithmetic coding is very competitive in short and medium block lengths. The existing distributed arithmetic coding decoder uses the maximum a posteriori metric and the M-algorithm to select the decoding sequence by considering the prior information. Since the prior probability distribution has been explored by the encoding process via the model stage and retained in the codeword, we propose a modified decoding metric ignoring the prior information. The reliability of the decoding paths is only determined by the correlation between the side information and the input source. Simulation results show that the modified metric can significantly reduce the decoding error. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICIP40778.2020.9190950 | 2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) |
Keywords | DocType | ISSN |
Slepian-Wolf coding, distributed arithmetic coding, arithmetic coding, distributed source coding | Conference | 1522-4880 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanchao Yang | 1 | 13 | 6.14 |
| Mingwei Qi | 2 | 0 | 0.34 |
| Junwei Zhou | 3 | 118 | 16.64 |
| Lee-Ming Cheng | 4 | 52 | 7.05 |