Title :
Image denoising algorithm via doubly local Wiener filtering with directional windows in wavelet domain
Author_Institution :
Nat. Lab. of Radar Signal Process., Xidian Univ., Xi´´an, China
Abstract :
Local Wiener filtering in the wavelet domain is an effective image denoising method of low complexity. In this letter, we propose a doubly local Wiener filtering algorithm, where the elliptic directional windows are used for different oriented subbands in order to estimate the signal variances of noisy wavelet coefficients, and the two procedures of local Wiener filtering are performed on the noisy image. The experimental results show that the proposed algorithm improves the denoising performance significantly.
Keywords :
Wiener filters; computational complexity; image denoising; wavelet transforms; doubly local Wiener filtering algorithm; elliptic directional window; image denoising algorithm; noisy wavelet coefficient; signal variance; wavelet domain; Clustering algorithms; Filtering algorithms; Image denoising; Noise reduction; Radar signal processing; Signal processing algorithms; Stochastic processes; Wavelet coefficients; Wavelet domain; Wiener filter; Doubly local Wiener filtering with directional window (DLWFDW); elliptic directional window; image denoising; local Wiener filtering with directional window (LWFDW);
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2005.855555