Name
Abstract | ||
|---|---|---|
This paper presents a performance analysis of measures used for assessing similarities between patches. Compared to subjective ground thruth, our results indicate that some metrics are more suitable than others in a context of patch matching. This conclusion is confirmed by an experiment on non-local means (NLM) denoising algorithm. The denoising quality depends on the chosen similarity metric. In the best case, the gain is of 1.3dB compared to a classical SSD-based denoising algorithm. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6638018 | 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
similarity metric, examplar-based, denoising | Noise reduction,Computer vision,Mathematical optimization,Denoising algorithm,Pattern recognition,Computer science,Non-local means,Image matching,Image denoising,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
7 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mounira Ebdelli | 1 | 45 | 2.00 |
| Olivier Le Meur | 2 | 476 | 36.14 |
| Christine Guillemot | 3 | 1286 | 104.25 |