摘要
类比值进行去噪是基于灰色系统理论的方法。根据图像中噪声像素的强度值与周围的非噪声像素比较起来有非常大的变化,而非噪声像素的强度值与周围像素值几乎近似的特点,依照类比的定义,根据噪声点对应的类比值较大,而非噪声点对应的类比值较小的特点,利用阈值方法可以准确的识别出图像的噪声点。
Image denoising is based on the values of class ratio is a method given in grey system theory. Since noises of an image correspond to intensity variation, the noise pixels are characterized with the strong variation in intensity values compared with the non-noise pixels, the intensity value of non-noise pixel is alike in the pixels around ,according to the definition of class ratio, the noise pixels results in larger class ratio while non-noise pixels result in small class ratio. Thresholding action is carried out to identify noise^point of image more accurate.
出处
《电子测量技术》
2009年第11期34-36,共3页
Electronic Measurement Technology
关键词
去噪
类比
图像处理
灰色系统理论
De-noise ,Class ratio , Image processing , Grey system theory
作者简介
宗庆梅，1984年出生，武汉理工大学数学系硕士研究生，主要研究方向数字图像处理。
桂预风，1963年出生。武汉理工大学教授，硕士导生师，主要研究方向为数字图像处理，数量经济学，统计学。E—mail：guiyufeng@hotmail．com
