图像滤波方法及其MATLAB实现

图像滤波方法及其MATLAB实现(论文13000字)
摘要：在数字图像处理中,由于受到成像方法的限制,图像中的边缘、细节特征等重要信息常湮没于噪声信号中,给图像的后继处理如边缘检测、图像分割、图像匹配等带来很大的影响。因此对含噪声图像进行适当的预处理是图像处理中的一个重要问题,对于改善图像质量具有重要的意义。图像去噪是图像预处理中一项应用比较广泛的技术,其作用是提高图像的信噪比,突出图像的期望区域.通过图像滤波对降质图像进行改善处理，去噪去模糊，最大限度还原成清晰高质的图像。本文主要对相关图像滤波算法的原理作了详细的论述,同时对不同算法设计了相关的Matlab程序对仿真图像进行验证。结果表明,改进算法较传统算法在性能上有所提升,既能有效去除噪声,又能保持图像细节特征。
关键词:图像滤波; 逆滤波; 均值滤波; 中值滤波; 改进后的中值滤波

Image filtering method and its MATLAB implementation
ABSTRACT：In digital image processing, due to the limitation of imaging method, important information of image， edges and details of the characteristics， often buried in noise signal,which will affect the post processing such as edge detection, image segmentation, image matching. Therefore, proper preprocessing of noisy images is essentialin image processingImage denoising is a widely used technology in image preprocessing , its role is to improve the image signal-to-noise ratio and enchance thedesired regions of  image. the quality of the imagecan be improved by image filtering. Denoise and deblur, try best to restore a high quality image.In this paper, the principle of the image filtering algorithm is discussed in detail, at the same time, the different programs are designed to evaluate effect in the Matlab. The results show that the improved algorithm has a better performance than the traditional algorithm, which can not only remove the noise effectively, but also keep the image details. [资料来源：www.THINK58.com]
Key words:image filtering;  inverse filtering;  mean filtering;  median filtering;  improved median filtering
  [资料来源：http://www.THINK58.com]

目 录
摘要    1
ABSTRACT    2
1  绪论    3
2 图像滤波概述    4
2.1 图像退化的原因及数学模型    4
2.1.1图像退化的原因    4
2.1.2图像退化和复原的数学模型    4
2.2 图像的噪声    5
2.2.1 噪声的分类    5
2.2.2 噪声的特征    8
2.2.3 噪声的算法    8
2.2.4 衡量滤波效果的重要参数    9
2.3 图像复原中的难点    9

3 空域滤波方法    10
3.1 逆滤波法    10
3.2 均值滤波    12
3.2.1 算术均值滤波器    12
3.2.2 几何均值滤波器    12
3.2.3 谐波均值滤波器    12
3.2.4 逆谐波均值滤波器    13
4 中值滤波    14
4.1 中值滤波的概述    14
4.2 传统中值滤波对椒盐噪声的算法    15
4.3 基于窗口移动的快速中值滤波    17
5 改进后的中值滤波    18
5.1加权的中值滤波    18
5.2 自适应中值滤波方法    19
6 总结    21
致谢    28 [资料来源：http://www.THINK58.com]