51 citations · 168 across the 23 of their papers we have counts for
6 papers · 1 filter
Audio Dequantization Using (Co)Sparse (Non)Convex Methods
Pavel Záviška, Pavel Rajmic, Ondřej Mokrý
The paper deals with the hitherto neglected topic of audio dequantization. It reviews the state-of-the-art sparsity-based approaches and proposes several new methods. Convex as wel…
A survey and an extensive evaluation of popular audio declipping methods
Pavel Záviška, Pavel Rajmic, Alexey Ozerov +1
Dynamic range limitations in signal processing often lead to clipping, or saturation, in signals. The task of audio declipping is estimating the original audio signal, given its cl…
Approximal operator with application to audio inpainting
Ondřej Mokrý, Pavel Rajmic
In their recent evaluation of time-frequency representations and structured sparsity approaches to audio inpainting, Lieb and Stark (2018) have used a particular mapping as a proxi…
Flexible framework for audio reconstruction
Ondřej Mokrý, Pavel Rajmic, Pavel Záviška
The paper presents a unified, flexible framework for the tasks of audio inpainting, declipping, and dequantization. The concept is further extended to cover analogous degradation m…
Sparse and Cosparse Audio Dequantization Using Convex Optimization
Pavel Záviška, Pavel Rajmic
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 r…
Audio Inpainting: Revisited and Reweighted
Ondřej Mokrý, Pavel Rajmic
We deal with the problem of sparsity-based audio inpainting, i.e. filling in the missing segments of audio. A consequence of the approaches based on mathematical optimization is th…