小波域中的广义非局部平均去噪算法

doi:10.3969/j.issn.1001-2400.2010.05.029

Abstract

Abstract:

The statistics of image wavelet coefficients is non-Gaussian and can be described by generalized Gaussian distribution (GGD). The paper investigates the issues of the GGD statistical model for wavelet coefficients in a subband and the corresponding parameter estimation. The estimated parameters are used to define a generalized nonlocal mean which allows us to restore the original image. A nonlocal mean denoising algorithm in the wavelet domain based on the GGD statistical model is proposed. Simulation results indicate that the proposed method outperforms the others by 1.5～3.3dB in the PSNR, and keeps a better visual result in edges information reservation as well.

Key words: wavelet coefficients, generalized Gaussian distribution, nonlocal means algorithm, image denoising

FENG Xiang-chu;LIU Tao;LI Ya-feng. Generalized nonlocal mean denoising research based on the wavelet domain[J].J4, 2010, 37(5): 941-946.

References

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Generalized nonlocal mean denoising research based on the wavelet domain

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