雷芸. 基于中值预滤波的非局部平均去噪算法[J]. 微电子学与计算机, 2015, 32(5): 138-142. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.029
引用本文: 雷芸. 基于中值预滤波的非局部平均去噪算法[J]. 微电子学与计算机, 2015, 32(5): 138-142. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.029
LEI Yun. Research of Image Denoising Algorithm Based on Non-local Priori Constraints[J]. Microelectronics & Computer, 2015, 32(5): 138-142. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.029
Citation: LEI Yun. Research of Image Denoising Algorithm Based on Non-local Priori Constraints[J]. Microelectronics & Computer, 2015, 32(5): 138-142. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.029

基于中值预滤波的非局部平均去噪算法

Research of Image Denoising Algorithm Based on Non-local Priori Constraints

  • 摘要: 传统基于非局部平均的去噪方法利用了高斯白噪声均值为零这一特点,只是简单加权平均来实现对像素点的估计.对于其他种类的噪声,加权平均往往不是一个合适的估计.结合中值滤波和预滤波法的思想,提出了基于中值预滤波的非局部平均去噪算法,很好地解决了非局部平均法对于椒盐噪声去除效果不理想的问题,同时还能兼顾去除高斯白噪声的性能.通过大量实验,给出了中值预滤波非局部平均法最优参数的选择建议.对于大多数图像,依据该策略进行参数选择可以得到较好的去噪效果.

     

    Abstract: Traditional Non-Local Means makes use of the characteristic of white Gaussian noise which has zero mean. This method only uses weighed mean as an estimator to evaluate each pixel. However, weighed mean is not an appropriate estimator for other kinds of noise. Hence, median filter is combined with pre-filtering and Median Pre-Filtering Non-Local Means is given out, whose denoising performance is pretty well in terms of both whit Gaussian noise and salt & pepper noise. In addition, a large quantities of experiments are conducted and some advices on choosing optimal parameters are proposed. As for most images, our advice can help the algorithm achieve great performance.

     

/

返回文章
返回