New method of image denoising based on fractional wavelet transform

Abstract

Nowadays, there are many mature image denoising methods, such as linear filtering and nonlinear filtering. In order to improve the denoising effect, a novel signal denoising method based on fractional wavelet transform (FRWT) is proposed in this paper. It combines the advantages of the fractional Fourier transform (FRFT) and the wavelet transforms (WT). By the simulation experiment, the optimal fractional order of FRWT is obtained with an iterative algorithm according to the PSNR of output signals. This method takes output peak signal to noise ratio (PSNR) and information entropy (IE) as the denoising evaluation index. The results of experiment show that the novel methods could effectively remove noise, and maintain information quantity maximally at the same time by adjusting the fractional order p and wavelet scale. © 2013 Springer Science+Business Media New York.