摘要
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。
A threshold de-noising method based on dyadic wavelet transform is proposed here based on the wavelet shrinkage put forword by D.L. Donoho and I.M. Johnstone. To analyze the de-noising performance of this method, de-noising experiments is conducted on the same image in different levels of Gaussian noise. The simulation results show that the threshold de-noising method based on dyadic wavelet transform not only suppresses the Gibbs phenomenon near the edge of the image effectively, but also it makes the peak signal to noise ratio of the de-noising images have a large extent improved at different noise levels, and have a very small range of fluctuation in different noise levels, which results indicate that de-noising performance of the threshold de-noising method based on dyadic wavelet transform has a strong stability.
出处
《计算机与现代化》
2010年第1期117-119,共3页
Computer and Modernization
基金
国家自然科学基金资助项目(10661010)
新疆维吾尔自治区自然科学基金资助项目(200721104)
