## 图像的滤波方法比较与MATLAB仿真实现

Abstract
In digital image processing, due to the limitation of the imaging method, the important information such as image edges and details often get lost in the noise signal, which brings great influenceto the subsequent image processing such as edge detection, image segmentation, image matching, etc.So proper pretreatment of image noise is an important problem in image processing, to improve the image quality is of great importance.    Image denoising is awide used image pretreatment technology, it is to improve the SNR of image, highlights the expectations of the image area.    Basically image noise reduction is the use of the distribution of noise and signal in the frequency domain.    Noise signals are mainly distributed in the low frequency region, and are mainly distributed in the high frequency regionas the same as the details of the image distribution in high frequency area.

This paper introduces the MATLAB basic operation function and the basic method of the functions, using the correlation function of image to add Gaussian noise, salt and pepper noise and use Butterworth low pass filtering, Gaussian high pass filter, Wiener filter and median filter to filter the three kinds of noise image. By analyzing and comparing the results, the understanding of various noise and Butterworth, Gauss high pass, median filtering and Wiener filter are deepened.
Key word: MATLAB   Image processing   Noise   Filter

1.绪论    8
1.1 MATLAB历史背景    8
1.2 MATLAB系统的主要组成部分    8
1.3 MATLAB的应用领域    9
1.4 MATLAB对数学运算的重要意义    10
1.5 MATLAB图像处理程序的开发特点    10
2.MATLAB基本运算    11
2.1 函数及运算    11
2.1.1极限运算    12
2.1.2微分计算    12
2.1.3积分的运算    13
2.1.4级数的运算    14
2.1.5 求解代数微分方程    14
2.1.6求解常微分方程    15
2.2矩阵相关运算    15
2.2.1矩阵的最大、最小值    15
2.2.2矩阵的均值    17
2.2.3矩阵的方差    18 图像的滤波方法比较与MATLAB仿真实现:http://www.lwfree.cn/zidonghua/20190421/32463.html
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