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A new image denoising algorithm based on nonsubsampled contourlet transform

机译:一种基于非非正宝型轮廓变换的新图像去噪算法

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A new postprocessing method based on nonsubsampled contourlet transform is introduced in this paper for suppressing additive Gaussian Noise (AWGN) in images. By transforming the noised image into nonsubsampled contourlet domain, the lowest-frequency subband is filtered by wiener filter firstly. According to the adaptive thresholds, the contourlet coefficients in different subbands are filtered. Experimental results show that our image denoising algorithm achieves the better performance than the traditional wiener filter method and the denoising algorithms based on wavelet or contourlet.
机译:本文介绍了一种基于非管道采样轮廓变换的新的后处理方法,用于抑制图像中的添加剂高斯噪声(AWGN)。 通过将声速图像转换为非管制的轮廓域,首先通过维纳滤波器过滤最低频率子带。 根据自适应阈值,滤波不同子带中的Contourlet系数。 实验结果表明,我们的图像去噪算法比传统的维纳滤波器方法和基于小波或轮廓件的去噪算法实现了更好的性能。

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