Declipping of audio signals using perceptual compressed sensing

Bruno Defraene, Naim Mansour, Steven De Hertogh, Toon Van Waterschoot, Moritz Diehl, Marc Moonen

Research output: Contribution to journalJournal articleResearchpeer-review


The restoration of clipped audio signals, commonly known as declipping, is important to achieve an improved level of audio quality in many audio applications. In this paper, a novel declipping algorithm is presented, jointly based on the theory of compressed sensing (CS) and on well-established properties of human auditory perception. Declipping is formulated as a sparse signal recovery problem using the CS framework. By additionally exploiting knowledge of human auditory perception, a novel perceptual compressed sensing (PCS) framework is devised. A PCS-based declipping algorithm is proposed which uses ℓ 1-norm type reconstruction. Comparative objective and subjective evaluation experiments reveal a significant audio quality increase for the proposed PCS-based declipping algorithm compared to CS-based declipping algorithms.

Original languageEnglish
Article number6600777
JournalIEEE Transactions on Audio, Speech and Language Processing
Issue number12
Pages (from-to)2627-2637
Number of pages11
Publication statusPublished - 2013
Externally publishedYes


  • Compressed sensing
  • declipping
  • perception
  • sparsity


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