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Wavelet-domain iterative center weighted median filter for image denoising

机译:小波域迭代中心加权中值滤波图像去噪

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摘要

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.
机译:提出了一种在小波系数域中称为迭代中心加权中值滤波器(ICWMF)的新中值滤波器,用于图像去噪。利用图像小波系数的尺度内和尺度间相关性,使用所提出的滤波器可以获得方差场的改进估计。该滤波器迭代地平滑噪声小波系数的方差,从而保留了包含在大幅度小波系数中的边缘信息。然后将使用ICWMF估计的方差字段用于最小均方误差估计器中,以对噪声图像小波系数进行消噪。仿真结果表明,与其他最近的图像去噪方法相比,可以获得更高的峰值信噪比。

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