Name
Abstract | ||
|---|---|---|
In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector quantized image are vulnerable to transmission or media impairments. Impulse block noise in the received images is the main artifact due to transmission errors. In this paper, we rue the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. fr reduces considerably the computational complexity at the receiver end. Simulation results show that the: proposed method considerably improves the subjective quality of VQ images transmitted over noisy channels. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/ICIP.1997.638761 | INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL II |
Keywords | DocType | Citations |
source code,interpolation,neural network,source coding,computational complexity,spatial context,vector quantization,set theory,noise,computational modeling,fuzzy set theory | Conference | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Basel Solaiman | 1 | 127 | 35.05 |
| Ramesh Pyndiah | 2 | 79 | 17.12 |
| Omar Aitsab | 3 | 0 | 0.34 |
| C Roux | 4 | 64 | 17.47 |