Signal Denoising Based on the Adaptive Shrinkage Function and Neighborhood characteristics

In order to provide more accurate and better denoising results, a novel denoising method based on an adaptive shrinkage function and neighborhood characteristics is proposed in this paper for one-dimensional signal. According to the number of large coefficients in neighborhoods of small coefficients, the small coefficients are shrunk term by term so as to preserve more useful information in detail coefficients. Several denoising experiments are performed in this paper. The optimal neighborhood size is selected to perform the more effective signal denoising. The visual perception of denoising signals shows that the proposed method can preserve information of original signal very well. Numerical results indicate that the proposed method is very effective and superior to hard thresholding, NeighShrink scheme and neighboring coefficients preservation scheme for almost all noise levels.