Adaptive Consistent Dictionary Learning for Audio Declipping

摘要

Clipping is a common problem in audio processing. Clipping distortion can be solved by the recently proposed consistent Dictionary Learning (cDL), but the performance of restoration will decrease when the clipping degree is large. To improve the performance of cDL, a method based on adaptive threshold is proposed. In this method, the clipping degree is estimated automatically, and the factor of the clipping degree is adjusted according to the degree of clipping. Experiments show the superior performance of the proposed algorithm with respect to cDL on audio signal restoration.