2 research outputs found

    Sparse representation for audio noise removal using zero-zone quantizers

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    In zero zone quantization, bins around zero are quantized to a zero value. This kind of quantization can be applied on orthogonal transforms to remove the unwanted or redundant signal. Transforms reveal structures and properties of a signal and hence careful application of a zero zone over the transform coefficients leads to noise removal. In this thesis, such quantizers are applied over Discrete Fourier Transform and Karhunen Loeve Transform coefficients separately, and outputs compared. Further, the localization of the zero zones to certain frequencies leads to better performance in terms of noise removal. PEAQ (Perceptual Evaluation of Audio Quality) scores have been used to measure the objective quality of the denoised signal
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