Abstract
This paper aims to acquire the crack information from the sound production images in vocal music in an accurate and comprehensive manner. Firstly, the image processing technology based on partial differential equations was introduced, and the principle of wavelet model was expounded. Considering the defects of the wavelet model, an improved wavelet model was constructed based on image enhancement function. The improved model was applied to process the sound production images in vocal music, which contain single crack or multiple cracks, respectively, producing high-quality binary images on the cracks of sound production in vocal music. The binary images were quantified to obtain the characteristic parameters of the sound source in vocal music, laying the basis for further research into sound production in vocal music. To verify its effectiveness, the improved wavelet model was compared with the traditional wavelet model through simulation experiment. The results show that the improved wavelet model achieved better image segmentation effect and quantified the microstructure of the sound source more accurately than the traditional wavelet model. Finally, the authors proved that the proposed model can be used to compute the coefficients of sound production with cracks and the damage variables of microstructure.
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For the paper above mentioned, on behalf of all the authors, I (we) declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of.
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He, J. Design and implementation of an improved wavelet model for processing sound production images in vocal music. Multimed Tools Appl 82, 21925–21939 (2023). https://doi.org/10.1007/s11042-020-10168-1
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DOI: https://doi.org/10.1007/s11042-020-10168-1