Denoising of Image and Audio by using Wavelet Transform

Abstract

This paper proposes real time de-noising algorithms for image and audio based on the Wavelet Transform. White noise is located in
all frequencies and is thus especially hard to detect. We use the locality of the wavelet function to single out the frequency domains of the signal
itself and thereby able to denoise it. Perfect denoising is not possible, the higher the threshold coefficient is set, the more the noise is detected,
but the more the original signal is affected as well. We have implemented a flexible framework for denoising that includes hard and soft
thresholding, different Wavelet Transforms and different treatments of the padding coefficients. The presented denoiser is a real-time application
that allows direct subjective judgements of a parameter setting.

Keywords: Image denoising, wavelet transform, hard thresholding and soft thresholding.