SIGNAL DENOISER USING WAVELETS AND BLOCK MATCHING PROCESS

Abstract

Noises present in signals are difficult to recover using the traditional methods. Now wavelet transform is used for denoising techniques. The thresholding both hard and soft are used in wavelet transform. But around discontinuities it creates Gibbs phenomenon. This is the main drawback of using wavelets. Here traditional method of total variation minimization is used for denoising in first step. The Gibbs oscillations are reduced using transformation domain and block matching is used for improvement of SNR. The technique exposes each and every finest details contributed by the grouped set of blocks and also it protects the vital and unique features of every individual block. The blocks are filtered and replaced in their original positions from where they are detached. A technique based on this denoising strategy and its efficient implementation is presented in full detail. The implementation results reveal that the proposed technique achieves a state-of-the-art denoising performance in terms of signal-to-noise ratio.