Audio signal deblurring using singular value decomposition (SVD)

Deblurring is the process of removing blurring artifacts from signals, such as blur caused by noise, defocus aberration or motion blur. Blind Convolution for signal separation is an area of research in the field of signal processing from last few decades. Similarly, image deblurring and restoration has also been an area of research using different techniques like Blind Signal Separation (BSS), Singular Value Decomposition (SVD) combined with DCT, DWT, Differential Evolution Optimization. However, very little research is been done on audio deblurring. In this paper, we proposed an idea for deblurring of an audio signal using SVD. At the end, we also computed root mean square error (RMSE), normalized root mean square error (NRMSE) and peak signal-to-noise ratio (PSNR) between the original audio signals and the signals retrieved after applying SVD.