Declipping of audio signals using perceptual compressed sensing

Research output: Contribution to journalJournal article – Annual report year: 2013Researchpeer-review

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  • Author: Defraene, Bruno

    KU Leuven

  • Author: Mansour, Naim

    KU Leuven

  • Author: De Hertogh, Steven

    KU Leuven

  • Author: Van Waterschoot, Toon

    KU Leuven

  • Author: Diehl, Moritz

    KU Leuven

  • Author: Moonen, Marc

    KU Leuven

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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
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Compressed sensing, declipping, perception, sparsity

ID: 140393238