Declipping of Audio Signals Using Perceptual Compressed Sensing

作者：Defraene Bruno^*; Mansour Naim; De Hertogh Steven; van Waterschoot Toon; Diehl Moritz; Moonen Marc

来源：IEEE Transactions on Audio Speech and Language Processing, 2013, 21(12): 2627-2637.

DOI：10.1109/TASL.2013.2281570

• Compressed sensing
• declipping
• perception
• sparsity

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.

• 出版日期2013-12