摘要
日常生活中,在发送、存储图像和拍照形成图像的过程中往往会因操作不当而导致图像不清晰,无法反映图像本质。为此采用图像降噪算法将图像中的杂质去除,还原出无噪声的图像,同时还可以使大部分的细节因素保留在图片中,让图片更加清晰。在去噪方法的运用上通常是采用无噪图像和含有噪声的先验信息,但弊端是二者并没有进行有效的结合。为了解决这个问题,采用小波、非局部均值等方式进行去噪,并且在非局部均值去噪中从欧氏距离和权重分配方面进行一些优化。
In the daily life,during the process of sending image,storing image,and taking photos to form images,improper operation often leads to unclear images that cannot reflect the essence of the image.To this end,an image denoising algorithm is used to remove impurities from the image,restoring a noise-free image.At the same time,most of the details can be retained in the image,making it clearer.In the application of denoising methods,noiseless images and prior information containing noise are usually used,but the drawback is that the two have not been effectively combined.To solve this problem,wavelet and non-local mean methods are used for denoising,and some optimizations are made in terms of Euclidean distance and weight allocation in non local mean denoising.
作者
白茹鑫
栾尚敏
BAI Ruxin;LUAN Shangmin(North China Institute of Science and Technology,Langfang 065201,China)
出处
《现代信息科技》
2024年第10期21-25,31,共6页
Modern Information Technology
关键词
图像去噪
小波去噪
非局部均值
欧氏距离
权重
image denoising
wavelet denoising
non-local mean
Euclidean distance
weight