Abstract
The problem of estimating the musical instrument sound signal, corrupted by additive white Gaussian noise has been of interest to many researchers for practical as well as theoretical reasons. The removal of white Gaussian noise is difficult as it persists at all the frequencies in the signal. Many of the methods, especially those based on wavelet technique have become popular, due to the number of advantages over the traditional methods. It has been shown that wavelet based thresholding is simple and optimal solution, also guarantees better rate of convergence. In this paper, a novel DWT based algorithm using block de-noising along with modified threshold is proposed. For experimental purpose, the sound signals of shehnai, dafli and flute are taken. The signal is first divided into the multiple blocks of samples and then both hard and soft thresholding methods are used on each block. All the blocks obtained after individual block de-noising are concatenated to get the final de-noised signal. When the sound signal corrupted with variable percentage of Gaussian noise, passed through this algorithm; significant improvement in PSNR is observed over normal wavelet thresholding method. The quality of sound signal obtained through this algorithm is perceptually close to original signal.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
