基于小波自适应阈值的图像去噪研究

Research on image denoising based on wavelet adaptive threshold

图像在采集、传输、接收和处理的过程中,不可避免地引入各种噪声,导致图像质量下降。降低图像在采集和传输等过程中产生的噪声,减少图像污染,是数字图像研究的重点。本文选用小波自适应模糊阈值法对图像进行去噪处理。选用了一种小波自适应模糊阈值去噪算法对图像进行多种阈值的设置进行图像自适应的去噪。得出在提取图像轮廓的基础上,较多地保持了图像的细节信息,极大地降低了图像的各种噪声。

In the process of collecting, transmitting, receiving and processing images, all kinds of noises are inevitably introduced, which leads to the decrease of image quality. To reduce the noise and reduce the image pollution in the process of collection and transmission is the focus of digital image research. In this paper, the wavelet adaptive fuzzy threshold method is used to denoise the image. A wavelet adaptive fuzzy threshold denoising algorithm is adopted to set the threshold of the image and to denoise the image adaptively. It is concluded that the detail information of the image is preserved more on the basis of extracting the contour of the image, and the noise of the image is greatly reduced.