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Sinusoidal modeling using frame-based perceptually weighted matching pursuits

We propose a method for sinusoidal modeling that takes into account the psychoacoustics of human hearing using a frame-based perceptually weighted matching pursuit. Working on blocks of the input signal, a set of sinusoidal components for each block is iteratively extracted taking into consideration perceptual significance by using extensions to the well known matching pursuits algorithm. These extensions allow including information about the time-varying masking threshold of the input signal during the pursuit. The blocks overlap-add together to reconstruct the entire signal. Although the perceptually weighted matching pursuit on each block can iterate until the error between the original and the reconstructed signal is zero, lower order approximations are possible by stopping the pursuit when the error becomes imperceptible to the human ear or by stopping the pursuit after a number of the perceptually most significant sinusoidal elements are found. The proposed sinusoidal model finds use in many applications including signal modifications and compression.