Wavelet-domain iterative center weighted median filter for image denoising

Abstract

A new median filter termed as the iterative center weighted median filter (ICWMF) in the wavelet coefficient domain is proposed for image denoising. Exploiting both inner- and inter-scale dependencies of the image wavelet coefficients, an improved estimation of the variance field is obtained using the proposed filter. This filter iteratively smoothes the noisy wavelet coefficients’ variances preserving the edge information contained in the large magnitude wavelet coefficients. The variance field estimated using the ICWMF is then used in a minimum mean-square error estimator to denoise the noisy image wavelet coefficients. Simulation results show that higher peak-signal-to-noise ratio can be obtained as compared to other recent image denoising methods.