| Autor: |
Záviška, Pavel, Rajmic, Pavel, Schimmel, Jíří |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
2019 42nd International Conference on Telecommunications and Signal Processing (TSP) |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1109/TSP.2019.8769109 |
| Popis: |
A novel method for audio declipping based on sparsity is presented. The method incorporates psychoacoustic information by weighting the transform coefficients in the $\ell_1$ minimization. Weighting leads to an improved quality of restoration while retaining a low complexity of the algorithm. Three possible constructions of the weights are proposed, based on the absolute threshold of hearing, the global masking threshold and on a quadratic curve. Experiments compare the restoration quality according to the signal-to-distortion ratio (SDR) and PEMO-Q objective difference grade (ODG) and indicate that with correctly chosen weights, the presented method is able to compete, or even outperform, the current state of the art. |
| Databáze: |
arXiv |
| Externí odkaz: |
|
