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在D.L.Donoho和I.M.Johnstone提出的小波阈值去噪方法的基础上,提出基于二进小波变换的阈值去噪方法。为分析此方法的去噪性能,对同一图像在叠加不同水平的Gaussian噪声的情况进行了去噪实验,仿真实验结果发现,基于二进小波变换的阈值去噪方法不但有效抑制了图像边缘附近的Gibbs现象,而且使去噪后图像的峰值信噪比在不同噪声水平下都有很大程度地改善,在不同噪声水平间有很小幅度的波动,这表明基于二进小波变换的阈值去噪方法的去噪性能具有很强的稳定性。
Based on the wavelet threshold denoising method proposed by D.L.Donoho and I.M. Johnstone, a threshold denoising method based on binary wavelet transform is proposed. In order to analyze the denoising performance of this method, the denoising experiments on the same image superimposed with different levels of Gaussian noise are carried out. The simulation results show that the threshold denoising method based on the binary wavelet transform not only effectively restrain the near-edge Gibbs phenomenon, and the peak signal-to-noise ratio of the denoised image is greatly improved at different noise levels with small amplitude fluctuations between different noise levels, which indicates that the threshold denoising based on the binary wavelet transform The denoising method has strong stability.