基于非局部均值算法的图像去噪方法研究

Image denoising methods based on the non-local means

针对图像中存在的噪声问题,利用非局部均值算法去除图像噪声,通过图像自身的冗余性和领域相似性,增强图像的几何空间结构信息,进而得到了较好的去噪效果。实验结果表明,在信噪比方面,非局部均值算法优于中值滤波算法。

Aiming at the noise problem existing in the image, the non-local mean algorithm is used to remove the image noise. The redundancy and domain similarity of the image are used to enhance the geometric spatial structure information of the image, and better denoising effect is obtained. The experimental results show that the non-local mean algorithm is superior to the median filtering algorithm in terms of signal-to-noise ratio.