基于不动点迭代算法的图像复原问题的研究
发布时间：2019-05-17 12:16
【摘要】：图像复原是数字图像处理领域一个重要的研究方向,其主要过程在于建立退化模型,将一幅待处理图像进行分析,恢复出原始图像.本学位论文主要将邻近域算子应用于图像去噪模型中,并对模型进行改进,构造出二阶导数模型和混合参数模型,并运用不动点迭代算法进行验证.其主要内容包括:第一章主要介绍了图像处理问题的研究背景和研究意义,简单的介绍了图像处理问题的几个重要方面和主要分支,并对本文的重点——图像复原问题的研究现状进行介绍.第二章介绍不动点迭代算法,利用此算法对ROF模型图像复原,接着对ROF模型改进,用二阶导来代替ROF模型中的正则项构造出新模型,给出不动点迭代算法和收敛条件,并进行验证和比较.第四章正则项用一阶和二阶混合,建立混合参数模型,给出不动点迭代算法收敛条件,并进行数值实验.实验结果表明:新模型在去噪效果上比传统去噪模型有所改进.
[Abstract]:Image restoration is an important research direction in the field of digital image processing. Its main process is to establish a degradation model, analyze an image to be processed, and restore the original image. In this thesis, the adjacent domain operator is mainly applied to the image denoising model, and the model is improved to construct the second derivative model and the mixed parameter model, and the fixed point iterative algorithm is used to verify the model. The main contents are as follows: the first chapter mainly introduces the research background and significance of image processing, and briefly introduces several important aspects and main branches of image processing. The research status of image restoration, which is the focus of this paper, is introduced. In the second chapter, the fixed point iterative algorithm is introduced, and then the ROF model is improved by using this algorithm to restore the image of the ROF model. The second derivative is used to replace the regular term in the ROF model to construct a new model, and the fixed point iterative algorithm and convergence conditions are given. And verify and compare. In chapter 4, the mixed parameter model is established by mixing the first order and the second order of the regular term, and the convergence conditions of the fixed point iterative algorithm are given, and the numerical experiments are carried out. The experimental results show that the denoising effect of the new model is better than that of the traditional denoising model.
【学位授予单位】：深圳大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：O177.91;TP391.41
本文编号：2479078
[Abstract]:Image restoration is an important research direction in the field of digital image processing. Its main process is to establish a degradation model, analyze an image to be processed, and restore the original image. In this thesis, the adjacent domain operator is mainly applied to the image denoising model, and the model is improved to construct the second derivative model and the mixed parameter model, and the fixed point iterative algorithm is used to verify the model. The main contents are as follows: the first chapter mainly introduces the research background and significance of image processing, and briefly introduces several important aspects and main branches of image processing. The research status of image restoration, which is the focus of this paper, is introduced. In the second chapter, the fixed point iterative algorithm is introduced, and then the ROF model is improved by using this algorithm to restore the image of the ROF model. The second derivative is used to replace the regular term in the ROF model to construct a new model, and the fixed point iterative algorithm and convergence conditions are given. And verify and compare. In chapter 4, the mixed parameter model is established by mixing the first order and the second order of the regular term, and the convergence conditions of the fixed point iterative algorithm are given, and the numerical experiments are carried out. The experimental results show that the denoising effect of the new model is better than that of the traditional denoising model.
【学位授予单位】：深圳大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：O177.91;TP391.41
【参考文献】
相关期刊论文 前1条
1 胡晓红;陈大卿;;基于变分偏微分方程的双参数图像去噪模型[J];重庆邮电大学学报(自然科学版);2012年03期
，本文编号：2479078
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