基于不動點迭代算法的圖像復原問題的研究
發(fā)布時間：2019-05-17 12:16
【摘要】：圖像復原是數(shù)字圖像處理領(lǐng)域一個重要的研究方向,其主要過程在于建立退化模型,將一幅待處理圖像進行分析,恢復出原始圖像.本學位論文主要將鄰近域算子應(yīng)用于圖像去噪模型中,并對模型進行改進,構(gòu)造出二階導數(shù)模型和混合參數(shù)模型,并運用不動點迭代算法進行驗證.其主要內(nèi)容包括:第一章主要介紹了圖像處理問題的研究背景和研究意義,簡單的介紹了圖像處理問題的幾個重要方面和主要分支,并對本文的重點——圖像復原問題的研究現(xiàn)狀進行介紹.第二章介紹不動點迭代算法,利用此算法對ROF模型圖像復原,接著對ROF模型改進,用二階導來代替ROF模型中的正則項構(gòu)造出新模型,給出不動點迭代算法和收斂條件,并進行驗證和比較.第四章正則項用一階和二階混合,建立混合參數(shù)模型,給出不動點迭代算法收斂條件,并進行數(shù)值實驗.實驗結(jié)果表明:新模型在去噪效果上比傳統(tǒng)去噪模型有所改進.
[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.
【學位授予單位】：深圳大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：O177.91;TP391.41
本文編號：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.
【學位授予單位】：深圳大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：O177.91;TP391.41
【參考文獻】
相關(guān)期刊論文 前1條
1 胡曉紅;陳大卿;;基于變分偏微分方程的雙參數(shù)圖像去噪模型[J];重慶郵電大學學報(自然科學版);2012年03期
，本文編號：2479078
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