基于非局部均值的图像去噪.doc

摘要 PAGE I 基于非局部均值的图像去噪 摘要 数字图像处理是年间数学技术和计算机交叉领域的一门新学科，图像去噪一直是该领域的研究热点，数字图像的有效去噪是图像信息预处理的关键步骤。在近二十年的研究中，涌现出许多去噪模型，主要有：高斯滤波，中值滤波，小波变换，均值滤波，双边滤波，非局部平均滤波等。随着对图像理解的不断深入和新教学理论的不断引入，图像去噪的方法与理论也不断得到丰富和发展。 本论文简要介绍了图像去噪的方法以及包括各方面的优点和不足，重点在研究非局部均值的图像去噪的具体算法与matlab的实现问题。首先是对图像去噪技术原理进行讨论从而引出两种传统的图像去噪技术即中值滤波及均值滤波，然后进行对非局部均值算法的详细讨论包括权值的计算，均值的实现以及对于有哪些信誉好的足球投注网站窗口的讨论。其次是对非局部均值图像去噪算法的matlab实现的讨论，包括算法实现过程的转换以及matlab实现的流程图。最后则是对仿真结果的分析，分别从两个角度进行了比较：同一图像在不同噪声下的PSNR（峰值信噪比），以及在同一噪声下不同的图像的PSNR比较，从而判断非局部均值图像去噪算法的去噪效果。 关键词　数字图像处理；图像处理；非局部均值 燕山大学本科生毕业设计（论文） 基于非局部均值的图像去噪 PAGE II PAGE II Abstract Digtial image processing is a new filed derived from mathematical technology and computer science.Image denoising is one of the widely discussed topic in this field.Effective denoising is critical for digital image information pre-processing.During two decades’development,variety of denosing models were proposed.such as Gaussian filtering .median filtering.wavelet transfor mation ,means filtering,non-local means filtering e.t.Image denoising as an important pre-processing step is always one of the research focuses in image processing and keeps continuous development . This paper briefly introduced the method of image denoising as well as various aspects including the strengths and weaknesses, with emphasis on non-local mean count image denoising specific issues and the realization of matlab. Along the following lines: First, the image denoising technique which leads to discussion of the two traditional image denoising technique that median filtering and mean filtering, and then proceed to non-local means algorithm, including a detailed discussion of the calculation of weights, mean to achieve, as well as for the discussion of the search window. Followed by the average of non-local algorithm for image denoising matlab discussions to achieve, including the process of conversion algorithm, as well as the realization of the flow chart of matlab. Finally, it is the analysis of simulation res