Sparse and Cosparse Audio Dequantization Using Convex Optimization
This is an incremental improvement for audio signal processing, offering better restoration of quantized signals.
The paper tackles audio dequantization by extending sparsity-based methods to include analysis models and different transforms, finding that the Gabor transform outperforms the cosine transform.
The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the range of the evaluation scenarios: we introduce the analysis (cosparse) model, we use more effective algorithms, we experiment with another time-frequency transform. The paper shows that the analysis-based model performs comparably to the synthesis-model, but the Gabor transform produces better results than the originally used cosine transform. Last but not least, we provide codes and data in a reproducible way.