activity
20142026
most citedA survey and an extensive evaluation of popular audio declipping methods

51 citations · 168 across the 23 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

math.OC2018

Image edges resolved well when using an overcomplete piecewise-polynomial model

Michaela Novosadová, Pavel Rajmic

Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robust…

cs.SD2018★ 28 cited

Introducing SPAIN (SParse Audio INpainter)

Ondřej Mokrý, Pavel Záviška, Pavel Rajmic +1

A novel sparsity-based algorithm for audio inpainting is proposed. It is an adaptation of the SPADE algorithm by Kitić et al., originally developed for audio declipping, to the tas…

eess.AS2018★ 23 cited

A Proper version of Synthesis-based Sparse Audio Declipper

Pavel Záviška, Pavel Rajmic, Ondřej Mokrý +1

Methods based on sparse representation have found great use in the recovery of audio signals degraded by clipping. The state of the art in declipping has been achieved by the SPADE…

math.OC2018★ 4 cited

S-SPADE Done Right: Detailed Study of the Sparse Audio Declipper Algorithms

Pavel Záviška, Ondřej Mokrý, Pavel Rajmic

This technical report shows and discusses in detail how Sparse Audio Declipper (SPADE) algorithms are derived from the signal model using the ADMM approach. The analysis version (A…

eess.AS2018★ 12 cited

Revisiting Synthesis Model of Sparse Audio Declipper

Pavel Záviška, Pavel Rajmic, Zdeněk Průša +1

The state of the art in audio declipping has currently been achieved by SPADE (SParse Audio DEclipper) algorithm by Kitić et al. Until now, the synthesis/sparse variant, S-SPADE, h…