一种新的非局部均值图像去噪方法

Zheng Haozhe, Jin Yunan, Lu Xiaomei
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引用次数: 1

摘要

提出了一种改进的分块非局部均值(BNL - means)方法来去除数字图像中的噪声。该方法包括高斯加权矩阵的谱分解、伪滤波器的构造、伪加权系数的计算以及高斯加权和的图像去噪。实验结果表明,该方法比传统的NL-means算法更简单、高效,对加性高斯白噪声下的自然图像和纹理图像去噪效果良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Non-local Means Method for Image Denoising
An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more efficient than the traditional NL-means algorithm and the denoising results are promising for the natural and textural image over the additive Gaussian white noise.
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