数字图像是采样和量化模拟图像得到的点阵图像，一副数字图像可以抽象为一个

A digital image is a dot matrix image obtained by sampling and quantizing an analog image. A digital image can be abstracted as a two-dimensional function f(x, y). The amplitude f of each position (x, y) in the image is called the position The gray value of, as shown in Equation 1, where N is the image resolution. <br>In a broad sense, noise refers to signals that hinder people's understanding of the original signal. The manifestation in the image affects people's understanding of digital images, and superimposes signals that interfere with people's vision on the image. Noise is random and unpredictable. Generally, the distribution function or probability density function in probability theory is used to describe its distribution characteristics. For ease of description, this article defines the following symbols: the original image signal is s, the noise signal is n, and the noisy image is f. According to the method of combining with signal, noise is divided into additive noise and multiplicative noise. Additive noise can generally be written as:

A digital image is a dot matrix image obtained by sampling and quantifying an analog image, a pair of digital images that can be abstracted into a two-dimensional function f (x,y), and the magnitude f of each position (x, y) in the image is called the grayscale value of that location, as shown in Formula 1, where N is the image resolution.<br>Noise in a broad sense is a signal that interferes with people's understanding of the original signal. Performance in the image affects people's understanding of digital images, superimposed on the image interferes with people's visual signals. Noise is random and unpredictable, and its distribution characteristics are generally described by the distribution function or probability density function in probability theory. For ease of description, this paper defines the following symbols: the original signal of the image is s, the noise signal is n, and the image containing noise is f. According to the combination with the signal, the noise is divided into added noise and multiplier noise, which can generally be written as:

Digital image is a lattice image obtained by sampling and quantizing analog image. A digital image can be abstracted as a two-dimensional function f (x, y). The amplitude F of each position (x, y) in the image is called the gray value of the position, as shown in Formula 1, where n is the image resolution.<br>In a broad sense, noise refers to the signal that hinders people's understanding of the original signal. Performance in the image that affects people's understanding of digital images, superimposed on the image to interfere with people's visual signal. Noise has randomness and unpredictability, and its distribution characteristics are generally described by the distribution function or probability density function in probability theory. For the convenience of description, this paper defines the following symbols: the original image signal is s, the noise signal is n, and the image with noise is f. According to the combination with signal, noise can be divided into additive noise and multiplicative noise<br>