图像高斯噪声滤波算法研究.doc
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本科毕业设计论文
题 目 图像高斯噪声滤波算法研究
专业名称 自动化
学生姓名 费 腾
指导教师 王红梅
毕业时间 2014年6月
毕业 任务书
一、题目
图像高斯噪声滤波算法研究
选题意义
图像处理是信息科学的主要组成部分,近年来图像处理理论与方法获得了迅猛的发展,而且在各个领域产生了重要的作用。目前,图像处理的方法主要有两大类:空间域法和频率域法,还有目前新兴的数学形态学和小波变换图像处理,以及独立分量分析方法。模拟噪声的行为和影响是图像去噪的核心。
三、指导思想和目的要求
本题目来源于科研,主要研究图像高斯噪声的特点,学习高斯加性噪声的滤波算法,进而编程实现相关算法。希望通过该毕业设计,学生能达到:
1.利用已有的专业知识,培养学生解决实际工程问题的能力;
2.锻炼学生的科研工作能力和培养学生团队合作及攻关能力。
1.;
2.;
3.。
期望能够解决实际工程问题,锻炼科研工作和培养团结合作攻关的能力。
六、进度和要求
第01周----第02周: 参考翻译英文文献;
第03周----第0周: 学习
第0周----第周: ; 第周----第14周: 编写;
第15周----第16周: 撰写毕业设计论文,论文答辩。赵书兰 化学工业出版社孙海英图像高斯噪声及椒盐噪声去噪算法研究王晓凯图像椒盐噪声及高斯噪声去噪方法研究ABSTRCT
Image processing is a major component of information science, image processing theory and methods in recent years has been rapid development, but also in various fields had an important role. Currently, the method of image processing are two major categories: spatial domain methods and frequency domain methods, there are currently emerging mathematical morphology and wavelet transform image processing, as well as independent component analysis. Behavior and the impact of noise is simulated image denoising core. The title comes from the research, the main research image Gaussian noise characteristics, high learning Alaska noise filtering algorithm, using neighborhood average, median, wavelet analysis to eliminate image noise. I focus on how the image Gaussian noise filtering methods are experimental, comparative and research papers main work is as follows:
1 discussed the meaning representation of digital images, the development of digital image processing, basic features, applications, and digital image filtering.
2 respectively neighborhood average value method and algorithm research and use neighborhood average and median denoising method Gaussian noise, the results of each method will be compared to make a summary.
Research study two-dimensional image wavelet transform decomposition and reconstruction, image using wavelet analy
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